Wrappers around srv_transform_teal_data that allows to decorate
-
Usage
+
Usage
srv_decorate_teal_data ( id , data , decorators , expr , expr_is_reactive = FALSE ) ui_decorate_teal_data ( id , decorators , ... )
-
Arguments
+
Arguments
-
id
+
+id
(character(1)) Module id
data
+data
(reactive teal_data)
expr
+expr
(expression or reactive) to evaluate on the output of the decoration.
When an expression it must be inline code. See within() NULL which won't evaluate any appending code.
expr_is_reactive
+expr_is_reactive
(logical(1)) whether expr is a reactive expression
that skips defusing the argument.
-
Details
+
Details
srv_decorate_teal_data is a wrapper around srv_transform_teal_data that
allows to decorate the data with additional expressions.
When original teal_data object is in error state, it will show that error
@@ -89,17 +135,19 @@
Substitute Names in a Quoted Expression — substitute_names • teal.modules.clinical Substitute Names in a Quoted Expression — substitute_names • teal.modules.clinical
+Skip to contents
@@ -17,24 +33,45 @@
+
+
@@ -53,7 +90,8 @@ Substitute Names in a Quoted Expression
-
Usage
+
Usage
substitute_names ( expr , names , others = list ( ) ) h_subst_lhs_names ( qexpr , names ) Usage
-
Arguments
+
Arguments
-
expr
+
+expr
(language)
names
+names
(named list of name)
others
+others
(named list)
qexpr
+qexpr
(language)
env
+env
(environment or list)
+
+
-
Value
+
Value
The modified expression.
-
Functions
+
Functions
-
Substitute in Quoted Expressions — substitute_q • teal.modules.clinical Substitute in Quoted Expressions — substitute_q • teal.modules.clinical
+Skip to contents
@@ -19,24 +35,45 @@
+
+
@@ -56,47 +93,58 @@ Substitute in Quoted Expressions
-
Arguments
+
Arguments
-
qexpr
+
+qexpr
(language)
env
+env
(environment or list)
-
Value
+
Value
The modified expression.
-
Note
+
Note
This is simplified from the package pryr to avoid another dependency.
teal Modules for Standard Clinical Outputs — teal.modules.clinical-package • teal.modules.clinical teal Modules for Standard Clinical Outputs — teal.modules.clinical-package • teal.modules.clinical
+Skip to contents
@@ -17,24 +33,45 @@
+
+
@@ -42,7 +79,8 @@
@@ -54,16 +92,24 @@ teal Modules for Standard Clinical Outputs
+
+
-
+
+
-
+
+
diff --git a/main/reference/template_a_gee.html b/main/reference/template_a_gee.html
index 77cd59eee..2c3e53f95 100644
--- a/main/reference/template_a_gee.html
+++ b/main/reference/template_a_gee.html
@@ -1,5 +1,21 @@
-
-Template for Generalized Estimating Equations (GEE) analysis module — template_a_gee • teal.modules.clinical Template for Generalized Estimating Equations (GEE) analysis module — template_a_gee • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template for Generalized Estimating Equations (GEE) analysis module
-
Usage
+
Usage
template_a_gee ( output_table ,
data_model_fit = "ANL" ,
@@ -69,79 +107,97 @@ Usage
-
Arguments
+
Arguments
-
output_table
+
+output_table
(character)"t_gee_cov", "t_gee_coef", "t_gee_lsmeans").
data_model_fit
+data_model_fit
(character)tern.gee::fit_gee()
dataname_lsmeans
+dataname_lsmeans
(character)alt_counts_df argument of rtables::build_table()
aval_var
+aval_var
(character)
id_var
+id_var
(character)
arm_var
+arm_var
(character)arm_var.
visit_var
+visit_var
(character)visit variable. Must be a factor in
dataname.
split_covariates
+split_covariates
(character)tern.gee::vars_gee()
cor_struct
+cor_struct
(character)tern.gee::fit_gee
conf_level
+conf_level
(numeric)
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Abnormality Summary Table — template_abnormality • teal.modules.clinical Template: Abnormality Summary Table — template_abnormality • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Abnormality Summary Table
-
Usage
+
Usage
template_abnormality ( parentname ,
dataname ,
@@ -73,109 +111,133 @@ Usage
-
Arguments
+
Arguments
-
parentname
+
+parentname
(character)ADSL.
dataname
+dataname
(character)
arm_var
+arm_var
(character)arm_var.
id_var
+id_var
(character)
by_vars
+by_vars
(character)
abnormal
+abnormal
(named list)
grade
+grade
(character)
baseline_var
+baseline_var
(character)
treatment_flag_var
+treatment_flag_var
(character)
treatment_flag
+treatment_flag
(character)treatment_flag_var.
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
exclude_base_abn
+exclude_base_abn
(logical)
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
na_level
+na_level
(character)"<Missing>".
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
tbl_title
+tbl_title
(character)
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Laboratory test results with highest grade post-baseline — template_abnormality_by_worst_grade • teal.modules.clinical Template: Laboratory test results with highest grade post-baseline — template_abnormality_by_worst_grade • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Laboratory test results with highest grade post-baseline
-
Usage
+
Usage
template_abnormality_by_worst_grade ( parentname ,
dataname ,
@@ -69,93 +107,113 @@ Usage
-
Arguments
+
Arguments
-
parentname
+
+parentname
(character)ADSL.
dataname
+dataname
(character)
arm_var
+arm_var
(character)arm_var.
id_var
+id_var
(character)
paramcd
+paramcd
(character)
atoxgr_var
+atoxgr_var
(character)
worst_high_flag_var
+worst_high_flag_var
(character)
worst_low_flag_var
+worst_low_flag_var
(character)
worst_flag_indicator
+worst_flag_indicator
(character)
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Patient Profile Adverse Events Table and Plot — template_adverse_events • teal.modules.clinical Template: Patient Profile Adverse Events Table and Plot — template_adverse_events • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Patient Profile Adverse Events Table and Plot
-
Usage
+
Usage
template_adverse_events ( dataname = "ANL" ,
aeterm = "AETERM" ,
@@ -67,77 +105,95 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
aeterm
+aeterm
(character)
tox_grade
+tox_grade
(character)
causality
+causality
(character)
outcome
+outcome
(character)
action
+action
(character)
time
+time
(character)
decod
+decod
(character)
patient_id
+patient_id
(character)
font_size
+font_size
(numeric)
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() teal.ggplot2_args and with default module arguments
(hard coded in the module body).
For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: ANCOVA Summary — template_ancova • teal.modules.clinical Template: ANCOVA Summary — template_ancova • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: ANCOVA Summary
-
Usage
+
Usage
template_ancova ( dataname = "ANL" ,
parentname = "ADSL" ,
@@ -75,117 +113,143 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
ref_arm
+ref_arm
(character)
comp_arm
+comp_arm
(character)
combine_comp_arms
+combine_comp_arms
(logical)
aval_var
+aval_var
(character)
label_aval
+label_aval
(character)
cov_var
+cov_var
(character)
include_interact
+include_interact
(logical)
interact_var
+interact_var
(character)NULL.
interact_y
+interact_y
(character)interact_var column which will be used to select the
specific ANCOVA results. If the interaction is not needed, the default option is FALSE.
paramcd_levels
+paramcd_levels
(character)
paramcd_var
+paramcd_var
(character)
label_paramcd
+label_paramcd
(character)
visit_levels
+visit_levels
(character)
visit_var
+visit_var
(character)visit variable. Must be a factor in
dataname.
conf_level
+conf_level
(numeric)
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Standard Template Arguments — template_arguments • teal.modules.clinical Standard Template Arguments — template_arguments • teal.modules.clinical
+Skip to contents
@@ -17,24 +33,45 @@
+
+
@@ -54,272 +91,335 @@ Standard Template Arguments
-
Arguments
+
Arguments
-
add_total
+
+add_total
(logical)
anl_name
+anl_name
(character)
arm_var
+arm_var
(character)arm_var.
atirel
+atirel
(character)
aval
+aval
aval_var argument instead.
avalu
+avalu
avalu_var argument instead.
avalu_var
+avalu_var
(character)
aval_var
+aval_var
(character)
baseline_var
+baseline_var
(character)
base_var
+base_var
baseline_var argument instead.
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
by_vars
+by_vars
(character)
cmdecod
+cmdecod
(character)
cmindc
+cmindc
(character)
cmstdy
+cmstdy
(character)
cnsr_var
+cnsr_var
(character)
combine_comp_arms
+combine_comp_arms
(logical)
compare_arm
+compare_arm
(logical)
comp_arm
+comp_arm
(character)
conf_level
+conf_level
(numeric)
control
+control
(list)
cov_var
+cov_var
(character)
dataname
+dataname
(character)
denominator
+denominator
(character)N, the reference
population from the column total is used as the denominator. With option n, the number of non-missing
records in this row and column intersection is used as the denominator. If omit is chosen, then the
percentage is omitted.
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
event_type
+event_type
(character)"event".
font_size
+font_size
(numeric)
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() teal.ggplot2_args and with default module arguments
(hard coded in the module body).
For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
hlt
+hlt
(character)
id_var
+id_var
(character)
include_interact
+include_interact
(logical)
label_hlt
+label_hlt
(string)hlt variable from dataname. The label will be extracted from the
module.
label_llt
+label_llt
(string)llt variable from dataname. The label will be extracted from the
module.
llt
+llt
(character)
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
na.rm
+na.rm
(logical)NA values should be removed prior to analysis.
numeric_stats
+numeric_stats
(character)n, mean_sd, mean_ci, median, median_ci, quantiles, range, and geom_mean.
paramcd
+paramcd
(character)
parentname
+parentname
(character)ADSL.
patient_id
+patient_id
(character)
prune_diff
+prune_diff
(number)
prune_freq
+prune_freq
(number)
ref_arm
+ref_arm
(character)
sort_criteria
+sort_criteria
(character)freq_desc sorts
on column sort_freq_col by decreasing number of patients with event. Alternative option alpha sorts events
alphabetically.
strata_var
+strata_var
(character)
subgroup_var
+subgroup_var
(character)
sum_vars
+sum_vars
(character)
time_points
+time_points
(character)tern::surv_timepoint()
time_unit_var
+time_unit_var
(character)
title
+title
(character)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
treatment_flag
+treatment_flag
(character)treatment_flag_var.
treatment_flag_var
+treatment_flag_var
(character)
useNA
+useNA
(character)NA) should be displayed as a level.
var_labels
+var_labels
(named character) optional
visit_var
+visit_var
(character)visit variable. Must be a factor in
dataname.
worst_flag_indicator
+worst_flag_indicator
(character)
worst_flag_var
+worst_flag_var
(character)
-
Value
+
Value
a list of expressions to generate a table or plot object.
-
Details
+
Details
Although this function just returns NULL it has two uses, for
the teal module users it provides a documentation of arguments that are
commonly and consistently used in the framework. For the developer it adds a
@@ -328,17 +428,19 @@
Template: Patient Profile Basic Info — template_basic_info • teal.modules.clinical Template: Patient Profile Basic Info — template_basic_info • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,47 +87,58 @@ Template: Patient Profile Basic Info
-
Usage
+
Usage
template_basic_info ( dataname = "ANL" , vars , patient_id = NULL )
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
vars
+vars
(character)
patient_id
+patient_id
(character)
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Binary Outcome — template_binary_outcome • teal.modules.clinical Template: Binary Outcome — template_binary_outcome • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Binary Outcome
-
Usage
+
Usage
template_binary_outcome ( dataname ,
parentname ,
@@ -75,107 +113,131 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
paramcd
+paramcd
(character)
ref_arm
+ref_arm
(character)
comp_arm
+comp_arm
(character)
compare_arm
+compare_arm
(logical)
combine_comp_arms
+combine_comp_arms
(logical)
aval_var
+aval_var
(character)
show_rsp_cat
+show_rsp_cat
(logical)
responder_val
+responder_val
(character)AVALC into responder/non-responder.
responder_val_levels
+responder_val_levels
(character)
control
+control
(list)
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Multi-Variable Cox Regression — template_coxreg_m • teal.modules.clinical Template: Multi-Variable Cox Regression — template_coxreg_m • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Multi-Variable Cox Regression
-
Usage
+
Usage
template_coxreg_m ( dataname ,
cov_var ,
@@ -70,92 +108,113 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
cov_var
+cov_var
(character)
arm_var
+arm_var
(character)arm_var.
cnsr_var
+cnsr_var
(character)
aval_var
+aval_var
(character)
ref_arm
+ref_arm
(character)
comp_arm
+comp_arm
(character)
paramcd
+paramcd
(character)
at
+at
(list of numeric)numeric type variable, use at
to specify the value of the covariate at which the effect should be estimated.
strata_var
+strata_var
(character)
combine_comp_arms
+combine_comp_arms
(logical)
control
+control
(list)tern::control_coxreg()
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Univariable Cox Regression — template_coxreg_u • teal.modules.clinical Template: Univariable Cox Regression — template_coxreg_u • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Univariable Cox Regression
-
Usage
+
Usage
template_coxreg_u ( dataname ,
cov_var ,
@@ -71,96 +109,118 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
cov_var
+cov_var
(character)
arm_var
+arm_var
(character)arm_var.
cnsr_var
+cnsr_var
(character)
aval_var
+aval_var
(character)
ref_arm
+ref_arm
(character)
comp_arm
+comp_arm
(character)
paramcd
+paramcd
(character)
at
+at
(list of numeric)numeric type variable, use at
to specify the value of the covariate at which the effect should be estimated.
strata_var
+strata_var
(character)
combine_comp_arms
+combine_comp_arms
(logical)
control
+control
(list)tern::control_coxreg()
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
append
+append
(logical)
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Events by Term — template_events • teal.modules.clinical Template: Events by Term — template_events • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Events by Term
-
Usage
+
Usage
template_events ( dataname ,
parentname ,
@@ -74,119 +112,144 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
hlt
+hlt
(character)
llt
+llt
(character)
label_hlt
+label_hlt
(string)hlt variable from dataname. The label will be extracted from the
module.
label_llt
+label_llt
(string)llt variable from dataname. The label will be extracted from the
module.
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
event_type
+event_type
(character)"event".
sort_criteria
+sort_criteria
(character)freq_desc sorts
on column sort_freq_col by decreasing number of patients with event. Alternative option alpha sorts events
alphabetically.
sort_freq_col
+sort_freq_col
(character)sort_criteria is set to freq_desc.
prune_freq
+prune_freq
(number)
prune_diff
+prune_diff
(number)
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
incl_overall_sum
+incl_overall_sum
(flag)
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Events by Grade — template_events_by_grade • teal.modules.clinical Template: Events by Grade — template_events_by_grade • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Events by Grade
-
Usage
+
Usage
template_events_by_grade ( dataname ,
parentname ,
@@ -73,112 +111,136 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
id
+id
(character)"USUBJID".
hlt
+hlt
(character)
llt
+llt
(character)
label_hlt
+label_hlt
(string)hlt variable from dataname. The label will be extracted from the
module.
label_llt
+label_llt
(string)llt variable from dataname. The label will be extracted from the
module.
grade
+grade
(character)
label_grade
+label_grade
(string)grade variable from dataname. The label will be extracted from the
module.
prune_freq
+prune_freq
(number)
prune_diff
+prune_diff
(number)
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Adverse Events Grouped by Grade with Threshold — template_events_col_by_grade • teal.modules.clinical Template: Adverse Events Grouped by Grade with Threshold — template_events_col_by_grade • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Adverse Events Grouped by Grade with Threshold
-
Usage
+
Usage
template_events_col_by_grade ( dataname ,
parentname ,
@@ -75,115 +113,140 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
grading_groups
+grading_groups
(list)
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
id
+id
(character)
hlt
+hlt
(character)
llt
+llt
(character)
label_hlt
+label_hlt
(string)hlt variable from dataname. The label will be extracted from the
module.
label_llt
+label_llt
(string)llt variable from dataname. The label will be extracted from the
module.
grade
+grade
(character)grading_groups on.
label_grade
+label_grade
(character)grade variable from dataname.
prune_freq
+prune_freq
(number)
prune_diff
+prune_diff
(number)
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Event Rates Adjusted for Patient-Years — template_events_patyear • teal.modules.clinical Template: Event Rates Adjusted for Patient-Years — template_events_patyear • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Event Rates Adjusted for Patient-Years
-
Usage
+
Usage
template_events_patyear ( dataname ,
parentname ,
@@ -68,88 +106,107 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
events_var
+events_var
(character)
label_paramcd
+label_paramcd
(character)paramcd variable text to use in the table title.
aval_var
+aval_var
(character)
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
control
+control
(list)
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Adverse Events Summary — template_events_summary • teal.modules.clinical Template: Adverse Events Summary — template_events_summary • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Adverse Events Summary
-
Usage
+
Usage
template_events_summary ( anl_name ,
parentname ,
@@ -73,113 +111,137 @@ Usage
-
Arguments
+
Arguments
-
anl_name
+
+anl_name
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
dthfl_var
+dthfl_var
(character)parentname.
Records with "Y" are summarized in the table row for "Total number of deaths".
dcsreas_var
+dcsreas_var
(character)parentname.
Records with "ADVERSE EVENTS" are summarized in the table row for
"Total number of patients withdrawn from study due to an AE".
flag_var_anl
+flag_var_anl
(character)dataset used to count adverse event sub-groups
(e.g. Serious events, Related events, etc.). Variable labels are used as table row names if they exist.
flag_var_aesi
+flag_var_aesi
(character)dataset used to count adverse event special
interest groups. All flag variables must be of type logical. Variable labels are used as table row names if
they exist.
aeseq_var
+aeseq_var
(character)dataset. Used for
counting total number of events.
llt
+llt
(character)
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
count_dth
+count_dth
(logical)dthfl_var). Defaults to TRUE.
count_wd
+count_wd
(logical)dcsreas_var). Defaults to TRUE.
count_subj
+count_subj
(logical)USUBJID). Only applies if
event flag variables are provided.
count_pt
+count_pt
(logical)llt). Only applies if
event flag variables are provided.
count_events
+count_events
(logical)aeseq_var). Only applies if event
flag variables are provided.
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Exposure Table for Risk management plan — template_exposure • teal.modules.clinical Template: Exposure Table for Risk management plan — template_exposure • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Exposure Table for Risk management plan
-
Usage
+
Usage
template_exposure ( parentname ,
dataname ,
@@ -72,104 +110,127 @@ Usage
-
Arguments
+
Arguments
-
parentname
+
+parentname
(character)ADSL.
dataname
+dataname
(character)
id_var
+id_var
(character)
paramcd
+paramcd
(character)
paramcd_label
+paramcd_label
(character)dataname dataset where the
value will be used to label the argument paramcd.
row_by_var
+row_by_var
(character)
col_by_var
+col_by_var
(character)
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
add_total_row
+add_total_row
(flag)total_row_label argument.
total_row_label
+total_row_label
(character)add_total_row).
drop_levels
+drop_levels
(flag)
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
aval_var
+aval_var
(character)
avalu_var
+avalu_var
(character)
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm • teal.modules.clinical Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Mixed Model Repeated Measurements (MMRM) Analysis
-
Usage
+
Usage
template_fit_mmrm ( parentname ,
dataname ,
@@ -93,148 +131,182 @@ Usage
-
Arguments
+
Arguments
-
parentname
+
+parentname
(character)ADSL.
dataname
+dataname
(character)
aval_var
+aval_var
(character)
arm_var
+arm_var
(character)arm_var.
ref_arm
+ref_arm
(character)
comp_arm
+comp_arm
(character)
combine_comp_arms
+combine_comp_arms
(logical)
id_var
+id_var
(character)
visit_var
+visit_var
(character)visit variable. Must be a factor in
dataname.
cov_var
+cov_var
(character)
conf_level
+conf_level
(numeric)
method
+method
(string)
cor_struct
+cor_struct
(string)"unstructured". See tern.mmrm::build_formula()
weights_emmeans
+weights_emmeans
argument from emmeans::emmeans()
parallel
+parallel
(flag)
fit_name
+fit_name
(string)
paramcd
+paramcd
(character)
show_relative
+show_relative
(string)control - treatment, default) or the "increase"
(treatment - control) be shown for the relative change from baseline.
table_type
+table_type
(string)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
lsmeans_plot
+lsmeans_plot
(named list)list of controls for LS means plot.
See more tern.mmrm::g_mmrm_lsmeans()
diagnostic_plot
+diagnostic_plot
(named list)list of controls for diagnostic_plot.
See more tern.mmrm::g_mmrm_diagnostic()
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() teal.ggplot2_args and with default module arguments
(hard coded in the module body).
For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
-
Functions
+
Functions
-
Template: Response Forest Plot — template_forest_rsp • teal.modules.clinical Template: Response Forest Plot — template_forest_rsp • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Response Forest Plot
-
Usage
+
Usage
template_forest_rsp ( dataname = "ANL" ,
parentname = "ADSL" ,
@@ -73,51 +111,67 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
ref_arm
+ref_arm
(character)
comp_arm
+comp_arm
(character)
obj_var_name
+obj_var_name
(character)
aval_var
+aval_var
(character)
responders
+responders
(character)aval_var that are considered to be responders.
subgroup_var
+subgroup_var
(character)
strata_var
+strata_var
(character)
stats
-(character)
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Survival Forest Plot — template_forest_tte • teal.modules.clinical Template: Survival Forest Plot — template_forest_tte • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Survival Forest Plot
-
Usage
+
Usage
template_forest_tte ( dataname = "ANL" ,
parentname = "ANL_ADSL" ,
@@ -74,51 +112,67 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
ref_arm
+ref_arm
(character)
comp_arm
+comp_arm
(character)
obj_var_name
+obj_var_name
(character)
aval_var
+aval_var
(character)
cnsr_var
+cnsr_var
(character)
subgroup_var
+subgroup_var
(character)
strata_var
+strata_var
(character)
stats
-(character)
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Confidence Interval Plot — template_g_ci • teal.modules.clinical Template: Confidence Interval Plot — template_g_ci • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Confidence Interval Plot
-
Usage
+
Usage
template_g_ci ( dataname ,
x_var ,
@@ -64,66 +102,81 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
x_var
+x_var
(character)
y_var
+y_var
(character)
grp_var
+grp_var
(character)
stat
+stat
(character)"mean" and "median".
conf_level
+conf_level
(numeric)
unit_var
+unit_var
(character)
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() teal.ggplot2_args and with default module arguments
(hard coded in the module body).
For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Individual Patient Plots — template_g_ipp • teal.modules.clinical Template: Individual Patient Plots — template_g_ipp • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Individual Patient Plots
-
Usage
+
Usage
template_g_ipp ( dataname = "ANL" ,
paramcd ,
@@ -73,104 +111,130 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
paramcd
+paramcd
(character)
arm_var
+arm_var
(character)arm_var.
arm_levels
+arm_levels
(character)arm_var.
avalu_first
+avalu_first
(character)avalu_var text to append to the plot title and y-axis label if add_avalu is
TRUE.
paramcd_first
+paramcd_first
(character)paramcd text to append to the plot title and y-axis label.
aval_var
+aval_var
(character)
avalu_var
+avalu_var
(character)
id_var
+id_var
(character)
visit_var
+visit_var
(character)
base_var
+base_var
baseline_var argument instead.
baseline_var
+baseline_var
(character)
add_baseline_hline
+add_baseline_hline
(logical)
separate_by_obs
+separate_by_obs
(logical)
ggplot2_args
-(ggplot2_args) optionalteal.widgets::ggplot2_args()
ggplot2_args
+
+(ggplot2_args) optionalteal.widgets::ggplot2_args() ggplot2_args object with labs list of
the following child elements: title, subtitle, x, y. No other elements are taken into account. The
argument is merged with option teal.ggplot2_args and with default module arguments (hard coded in the module
body).
-For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+
-suppress_legend
+suppress_legend
(logical)
add_avalu
+add_avalu
(logical)avalu_first text should be appended to the plot title and y-axis label.
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Kaplan-Meier Plot — template_g_km • teal.modules.clinical Template: Kaplan-Meier Plot — template_g_km • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Kaplan-Meier Plot
-
Usage
+
Usage
template_g_km ( dataname = "ANL" ,
arm_var = "ARM" ,
@@ -86,166 +124,203 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
arm_var
+arm_var
(character)arm_var.
ref_arm
+ref_arm
(character)
comp_arm
+comp_arm
(character)
compare_arm
+compare_arm
(logical)
combine_comp_arms
+combine_comp_arms
(logical)
aval_var
+aval_var
(character)
cnsr_var
+cnsr_var
(character)
xticks
+xticks
(numeric or NULL)NULL (default), labeling::extended()
strata_var
+strata_var
(character)
time_points
+time_points
(character)tern::surv_timepoint()
facet_var
+facet_var
(character)
font_size
+font_size
(numeric)
conf_level
+conf_level
(numeric)
ties
+ties
(string)exact (equivalent to DISCRETE in SAS), efron and breslow,
see survival::coxph() EXACT method in R.
xlab
+xlab
(string)
time_unit_var
+time_unit_var
(character)
yval
+yval
(string)Survival (default) and Failure
probability.
ylim
+ylim
(numeric(2))NULL (default), the default scale range is used.
pval_method
+pval_method
(string)wald (default) or likelihood.
annot_surv_med
+annot_surv_med
(flag)
annot_coxph
+annot_coxph
(flag)survival::coxph()
control_annot_surv_med
+control_annot_surv_med
(list)annot_surv_med = TRUE, specified using the control_surv_med_annot() x, y, w, h, and fill. See control_surv_med_annot()
control_annot_coxph
+control_annot_coxph
(list)annot_coxph = TRUE, specified using the control_coxph_annot() x, y, w, h, fill, and ref_lbls. See control_coxph_annot()
legend_pos
+legend_pos
(numeric(2) or NULL)NULL (default), the legend is positioned in the bottom right corner of
the plot, or the middle right of the plot if needed to prevent overlapping.
position_coxph
+position_coxph
x and y elements of
control_annot_coxph instead.
width_annots
+width_annots
w element of control_annot_surv_med
(for surv_med) and control_annot_coxph (for coxph)."
rel_height_plot
+rel_height_plot
(proportion)1 - rel_height_plot. If annot_at_risk = FALSE or
as_list = TRUE, this parameter is ignored.
ci_ribbon
+ci_ribbon
(flag)
title
+title
(character)
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Line Plot — template_g_lineplot • teal.modules.clinical Template: Line Plot — template_g_lineplot • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Line Plot
-
Usage
+
Usage
template_g_lineplot ( dataname = "ANL" ,
strata = lifecycle :: deprecated ( ) ,
@@ -76,125 +114,154 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
strata
+strata
group_var argument instead.
group_var
+group_var
(string or NA)
x
+x
(string)
y
+y
(string)
y_unit
+y_unit
(string or NA)
paramcd
+paramcd
(string or NA)
param
+param
(character)
mid
+mid
(character or NULL)mid variable must be present in the object returned by sfun,
and be of a double or numeric type vector of length one.
interval
+interval
(character or NULL)interval variable must be present in the object returned by sfun,
and be of a double or numeric type vector of length two. Set interval = NULL if intervals should not be
added to the plot.
whiskers
+whiskers
(character)interval that will be returned by sfun (e.g. mean_ci_lwr element of
sfun(x)[["mean_ci"]]). It is possible to specify one whisker only, or to suppress all whiskers by setting
interval = NULL.
table
+table
(character or NULL)table variable must be present in the object returned by sfun.
mid_type
+mid_type
(string)mid plot, it can be point ("p"), line ("l"),
or point and line ("pl").
conf_level
+conf_level
(numeric)
incl_screen
+incl_screen
(logical)
mid_point_size
+mid_point_size
(numeric(1))mid plot points.
table_font_size
+table_font_size
(numeric(1))
title
+title
(string)
y_lab
+y_lab
(string or NULL)NULL then no label will be added.
ggplot2_args
-(ggplot2_args) optionalteal.widgets::ggplot2_args()
ggplot2_args
+
+(ggplot2_args) optionalteal.widgets::ggplot2_args() ggplot2_args object with labs list of
following child elements: title, subtitle, caption, y, lty. No other elements would be taken into
account. The argument is merged with option teal.ggplot2_args and with default module arguments (hard coded in
the module body).
-For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+
-
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Patient Profile Laboratory Table — template_laboratory • teal.modules.clinical Template: Patient Profile Laboratory Table — template_laboratory • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Patient Profile Laboratory Table
-
Usage
+
Usage
template_laboratory ( dataname = "ANL" ,
paramcd = "PARAMCD" ,
@@ -67,74 +105,92 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
paramcd
+paramcd
(character)
param
+param
(character)
anrind
+anrind
(character)
timepoints
+timepoints
(character)
aval
+aval
aval_var argument instead.
aval_var
+aval_var
(character)
avalu
+avalu
avalu_var argument instead.
avalu_var
+avalu_var
(character)
patient_id
+patient_id
(character)
round_value
+round_value
(numeric)
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Logistic Regression — template_logistic • teal.modules.clinical Template: Logistic Regression — template_logistic • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Logistic Regression
-
Usage
+
Usage
template_logistic ( dataname ,
arm_var ,
@@ -71,94 +109,116 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
arm_var
+arm_var
(character)arm_var. To fit a logistic model with no
arm/treatment variable, set to NULL.
aval_var
+aval_var
(character)
paramcd
+paramcd
paramcd argument is not used in this function.
label_paramcd
+label_paramcd
(character)
cov_var
+cov_var
(character)
interaction_var
+interaction_var
(character)
ref_arm
+ref_arm
(character)
comp_arm
+comp_arm
(character)
topleft
+topleft
(character)
conf_level
+conf_level
(numeric)
combine_comp_arms
+combine_comp_arms
(logical)
responder_val
+responder_val
(character)
at
+at
(numeric or NULL)
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Patient Profile Medical History — template_medical_history • teal.modules.clinical Template: Patient Profile Medical History — template_medical_history • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Patient Profile Medical History
-
Usage
+
Usage
template_medical_history ( dataname = "ANL" ,
mhterm = "MHTERM" ,
@@ -61,50 +99,62 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
mhterm
+mhterm
(character)
mhbodsys
+mhbodsys
(character)
mhdistat
+mhdistat
(character)
patient_id
+patient_id
(character)
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Multiple Events by Term — template_mult_events • teal.modules.clinical Template: Multiple Events by Term — template_mult_events • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Multiple Events by Term
-
Usage
+
Usage
template_mult_events ( dataname ,
parentname ,
@@ -68,90 +106,109 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
seq_var
+seq_var
(character)
hlt
+hlt
(character)
llt
+llt
(character)
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
event_type
+event_type
(character)"event".
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Patient Profile Timeline Plot — template_patient_timeline • teal.modules.clinical Template: Patient Profile Timeline Plot — template_patient_timeline • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Patient Profile Timeline Plot
-
Usage
+
Usage
template_patient_timeline ( dataname = "ANL" ,
aeterm = "AETERM" ,
@@ -71,93 +109,115 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
aeterm
+aeterm
(character)
aetime_start
+aetime_start
(character)
aetime_end
+aetime_end
(character)
dstime_start
+dstime_start
(character)
dstime_end
+dstime_end
(character)
cmdecod
+cmdecod
(character)
aerelday_start
+aerelday_start
(character)
aerelday_end
+aerelday_end
(character)
dsrelday_start
+dsrelday_start
(character)
dsrelday_end
+dsrelday_end
(character)
relative_day
+relative_day
(logical)TRUE) or absolute dates (FALSE).
patient_id
+patient_id
(character)
font_size
+font_size
(numeric)
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() teal.ggplot2_args and with default module arguments
(hard coded in the module body).
For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Patient Profile Prior Medication — template_prior_medication • teal.modules.clinical Template: Patient Profile Prior Medication — template_prior_medication • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Patient Profile Prior Medication
-
Usage
+
Usage
template_prior_medication ( dataname = "ANL" ,
atirel = "ATIREL" ,
@@ -61,50 +99,62 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
atirel
+atirel
(character)
cmdecod
+cmdecod
(character)
cmindc
+cmindc
(character)
cmstdy
+cmstdy
(character)
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Shift by Arm — template_shift_by_arm • teal.modules.clinical Template: Shift by Arm — template_shift_by_arm • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Shift by Arm
-
Usage
+
Usage
template_shift_by_arm ( dataname ,
parentname ,
@@ -71,99 +109,121 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
paramcd
+paramcd
(character)
visit_var
+visit_var
(character)visit variable. Must be a factor in
dataname.
treatment_flag_var
+treatment_flag_var
(character)
treatment_flag
+treatment_flag
(character)treatment_flag_var.
aval_var
+aval_var
(character)
base_var
+base_var
baseline_var argument instead.
baseline_var
+baseline_var
(character)
na.rm
+na.rm
(logical)NA values should be removed prior to analysis.
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Shift by Arm by Worst Analysis Indicator Level — template_shift_by_arm_by_worst • teal.modules.clinical Template: Shift by Arm by Worst Analysis Indicator Level — template_shift_by_arm_by_worst • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Shift by Arm by Worst Analysis Indicator Level
-
Usage
+
Usage
template_shift_by_arm_by_worst ( dataname ,
parentname ,
@@ -72,102 +110,125 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
paramcd
+paramcd
(character)
worst_flag_var
+worst_flag_var
(character)
worst_flag
+worst_flag
(character)
treatment_flag_var
+treatment_flag_var
(character)
treatment_flag
+treatment_flag
(character)treatment_flag_var.
aval_var
+aval_var
(character)
base_var
+base_var
baseline_var argument instead.
baseline_var
+baseline_var
(character)
na.rm
+na.rm
(logical)NA values should be removed prior to analysis.
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Grade Summary Table — template_shift_by_grade • teal.modules.clinical Template: Grade Summary Table — template_shift_by_grade • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Grade Summary Table
-
Usage
+
Usage
template_shift_by_grade ( parentname ,
dataname ,
@@ -72,105 +110,128 @@ Usage
-
Arguments
+
Arguments
-
parentname
+
+parentname
(character)ADSL.
dataname
+dataname
(character)
arm_var
+arm_var
(character)arm_var.
id_var
+id_var
(character)
visit_var
+visit_var
(character)visit variable. Must be a factor in
dataname.
worst_flag_var
+worst_flag_var
(character)
worst_flag_indicator
+worst_flag_indicator
(character)
anl_toxgrade_var
+anl_toxgrade_var
(character)
base_toxgrade_var
+base_toxgrade_var
(character)
paramcd
+paramcd
(character)
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
code_missing_baseline
+code_missing_baseline
(logical)
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Adverse Events Table by Standardized MedDRA Query — template_smq • teal.modules.clinical Template: Adverse Events Table by Standardized MedDRA Query — template_smq • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Adverse Events Table by Standardized MedDRA Query
-
Usage
+
Usage
template_smq ( dataname ,
parentname ,
@@ -69,94 +107,114 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
llt
+llt
(character)
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
sort_criteria
+sort_criteria
(character)freq_desc sorts
on column sort_freq_col by decreasing number of patients with event. Alternative option alpha sorts events
alphabetically.
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
smq_varlabel
+smq_varlabel
(character)SMQ created by tern::h_stack_by_baskets()
baskets
+baskets
(character)
id_var
+id_var
(character)
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Summary of Variables — template_summary • teal.modules.clinical Template: Summary of Variables — template_summary • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Summary of Variables
-
Usage
+
Usage
template_summary ( dataname ,
parentname ,
@@ -72,105 +110,127 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
sum_vars
+sum_vars
(character)
show_labels
+show_labels
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
var_labels
+var_labels
(named character) optional
arm_var_labels
+arm_var_labels
(character or NULL)arm_var. If NULL, no labels will be displayed.
na.rm
+na.rm
(logical)NA values should be removed prior to analysis.
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
numeric_stats
+numeric_stats
(character)n, mean_sd, mean_ci, median, median_ci, quantiles, range, and geom_mean.
denominator
+denominator
(character)N, the reference
population from the column total is used as the denominator. With option n, the number of non-missing
records in this row and column intersection is used as the denominator. If omit is chosen, then the
percentage is omitted.
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Summarize Variables by Row Groups Module — template_summary_by • teal.modules.clinical Template: Summarize Variables by Row Groups Module — template_summary_by • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Summarize Variables by Row Groups Module
-
Usage
+
Usage
template_summary_by ( parentname ,
dataname ,
@@ -75,117 +113,142 @@ Usage
-
Arguments
+
Arguments
-
parentname
+
+parentname
(character)ADSL.
dataname
+dataname
(character)
arm_var
+arm_var
(character)arm_var.
id_var
+id_var
(character)
sum_vars
+sum_vars
(character)
by_vars
+by_vars
(character)
var_labels
+var_labels
(named character) optional
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
parallel_vars
+parallel_vars
(logical)TRUE if all chosen analysis variables are numeric.
row_groups
+row_groups
(logical)
na.rm
+na.rm
(logical)NA values should be removed prior to analysis.
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
numeric_stats
+numeric_stats
(character)n, mean_sd, mean_ci, median, median_ci, quantiles, range, and geom_mean.
denominator
+denominator
(character)N, the reference
population from the column total is used as the denominator. With option n, the number of non-missing
records in this row and column intersection is used as the denominator. If omit is chosen, then the
percentage is omitted.
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
drop_zero_levels
+drop_zero_levels
(logical)
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Patient Profile Therapy Table and Plot — template_therapy • teal.modules.clinical Template: Patient Profile Therapy Table and Plot — template_therapy • teal.modules.clinical
+Skip to contents
@@ -17,24 +33,45 @@
+
+
@@ -53,7 +90,8 @@ Template: Patient Profile Therapy Table and Plot
-
Usage
+
Usage
template_therapy ( dataname = "ANL" ,
atirel = "ATIREL" ,
@@ -73,89 +111,110 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
atirel
+atirel
(character)
cmdecod
+cmdecod
(character)
cmindc
+cmindc
(character)
cmdose
+cmdose
(character)
cmtrt
+cmtrt
(character)
cmdosu
+cmdosu
(character)
cmroute
+cmroute
(character)
cmdosfrq
+cmdosfrq
(character)
cmstdy
+cmstdy
(character)
cmendy
+cmendy
(character)
patient_id
+patient_id
(character)
font_size
+font_size
(numeric)
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() teal.ggplot2_args and with default module arguments
(hard coded in the module body).
For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Time-To-Event — template_tte • teal.modules.clinical Template: Time-To-Event — template_tte • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Time-To-Event
-
Usage
+
Usage
template_tte ( dataname = "ANL" ,
parentname = "ADSL" ,
@@ -75,113 +113,139 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(character)arm_var.
paramcd
+paramcd
(character)
ref_arm
+ref_arm
(character)
comp_arm
+comp_arm
(character)
compare_arm
+compare_arm
(logical)
combine_comp_arms
+combine_comp_arms
(logical)
aval_var
+aval_var
(character)
cnsr_var
+cnsr_var
(character)
strata_var
+strata_var
(character)
time_points
+time_points
(character)tern::surv_timepoint()
time_unit_var
+time_unit_var
(character)
event_desc_var
+event_desc_var
(character)
control
+control
(list)control_tte()
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
Template: Patient Profile Vitals Plot — template_vitals • teal.modules.clinical Template: Patient Profile Vitals Plot — template_vitals • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Template: Patient Profile Vitals Plot
-
Usage
+
Usage
template_vitals ( dataname = "ANL" ,
paramcd = "PARAMCD" ,
@@ -65,69 +103,85 @@ Usage
-
Arguments
+
Arguments
-
dataname
+
+dataname
(character)
paramcd
+paramcd
(character)
paramcd_levels
+paramcd_levels
(character)paramcd.
xaxis
+xaxis
(character)
aval
+aval
aval_var argument instead.
aval_var
+aval_var
(character)
patient_id
+patient_id
(character)
font_size
+font_size
(numeric)
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() teal.ggplot2_args and with default module arguments
(hard coded in the module body).
For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+
+
-
Value
+
Value
a list of expressions to generate a table or plot object.
teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee • teal.modules.clinical teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Generalized Estimating Equations (GEE) analysis
-
Usage
+
Usage
tm_a_gee ( label ,
dataname ,
@@ -73,49 +111,60 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
aval_var
+aval_var
(teal.transform::choices_selected()
id_var
+id_var
(teal.transform::choices_selected()
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
visit_var
+visit_var
(teal.transform::choices_selected() visit variable.
Must be a factor in dataname.
cov_var
+cov_var
(teal.transform::choices_selected()
arm_ref_comp
+arm_ref_comp
(list) optional,ADSL and the element must be another list (possibly
with delayed teal.transform::variable_choices() teal.transform::value_choices()
Argumentsparamcd paramcd
(teal.transform::choices_selected() dataname.
conf_level
+conf_level
(teal.transform::choices_selected()
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
library ( dplyr ) #> #> Attaching package: ‘dplyr’
+
+
teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm • teal.modules.clinical teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Mixed Model Repeated Measurements (MMRM) Analysis
-
Usage
+
Usage
tm_a_mmrm ( label ,
dataname ,
@@ -79,49 +117,60 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
aval_var
+aval_var
(teal.transform::choices_selected()
id_var
+id_var
(teal.transform::choices_selected()
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
visit_var
+visit_var
(teal.transform::choices_selected() visit variable.
Must be a factor in dataname.
cov_var
+cov_var
(teal.transform::choices_selected()
arm_ref_comp
+arm_ref_comp
(list) optional,ADSL and the element must be another list (possibly
with delayed teal.transform::variable_choices() teal.transform::value_choices()
Argumentsparamcd paramcd
(teal.transform::choices_selected() dataname.
method
+method
(teal.transform::choices_selected()
conf_level
+conf_level
(teal.transform::choices_selected()
plot_height
+plot_height
(numeric) optionalc(value, min, max). Specifies the
height of the main plot and renders a slider on the plot to interactively adjust the plot height.
plot_width
+plot_width
(numeric) optionalc(value, min, max). Specifies the width
of the main plot and renders a slider on the plot to interactively adjust the plot width.
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() ggplot2_args objects for plot-specific settings.
List names should match the following: c("default", "lsmeans", "diagnostic"). The argument is merged
@@ -185,42 +244,54 @@
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Note
+
Note
The ordering of the input data sets can lead to slightly different numerical results or
different convergence behavior. This is a known observation with the used package
lme4. However, once convergence is achieved, the results are reliable up to
numerical precision.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
lsmeans_plot (ggplot2)
This module generates the following objects, which can be modified in place using decorators:
+Decorators can be applied to all outputs or only to specific objects using a
+
+
Decorators can be applied to all outputs or only to specific objects using a
named list of teal_transform_module objects.
The "default" name is reserved for decorators that are applied to all outputs.
See code snippet below:
-
tm_a_mrmm (
+
+
tm_a_mrmm (# arguments for module decorators = list (default = list (teal_transform_module (...)), # applied to all outputs Decorating Modulefixed_effects_table = list (teal_transform_module (...)) # applied only to `fixed_effects_table` output
diagnostic_table = list (teal_transform_module (...)) # applied only to `diagnostic_table` output
+
+
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple • teal.modules.clinical teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Simple Bar Chart and Table of Counts per Category
-
Usage
+
Usage
tm_g_barchart_simple ( x = NULL ,
fill = NULL ,
@@ -68,105 +106,133 @@ Usage
-
Arguments
+
Arguments
-
x
+
+x
(data_extract_spec)
fill
+fill
(data_extract_spec)
x_facet
+x_facet
(data_extract_spec)
y_facet
+y_facet
(data_extract_spec)
label
+label
(character)
plot_options
+plot_options
(list)
plot_height
+plot_height
(numeric) optionalc(value, min, max). Specifies the
height of the main plot and renders a slider on the plot to interactively adjust the plot height.
plot_width
+plot_width
(numeric) optionalc(value, min, max). Specifies the width
of the main plot and renders a slider on the plot to interactively adjust the plot width.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() teal.ggplot2_args and with default module arguments
(hard coded in the module body).
For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Details
+
Details
Categories can be defined up to four levels deep and are defined through the x, fill,
x_facet, and y_facet parameters. Any parameters set to NULL (default) are ignored.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Confidence Interval Plot — tm_g_ci • teal.modules.clinical teal Module: Confidence Interval Plot — tm_g_ci • teal.modules.clinical
+Skip to contents
@@ -17,24 +33,45 @@
+
+
@@ -53,7 +90,8 @@ teal Module: Confidence Interval Plot
-
Usage
+
Usage
tm_g_ci ( label ,
x_var ,
@@ -72,101 +110,128 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
x_var
+x_var
(character)
y_var
+y_var
(character)
color
+color
(data_extract_spec)
stat
+stat
(character)"mean" and "median".
conf_level
+conf_level
(teal.transform::choices_selected()
plot_height
+plot_height
(numeric) optionalc(value, min, max). Specifies the
height of the main plot and renders a slider on the plot to interactively adjust the plot height.
plot_width
+plot_width
(numeric) optionalc(value, min, max). Specifies the width
of the main plot and renders a slider on the plot to interactively adjust the plot width.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() teal.ggplot2_args and with default module arguments
(hard coded in the module body).
For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Forest Response Plot — tm_g_forest_rsp • teal.modules.clinical teal Module: Forest Response Plot — tm_g_forest_rsp • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Forest Response Plot
-
Usage
+
Usage
tm_g_forest_rsp ( label ,
dataname ,
@@ -82,28 +120,35 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
arm_ref_comp
+arm_ref_comp
(list) optional,ADSL and the element must be another list (possibly
with delayed teal.transform::variable_choices() teal.transform::value_choices()
Argumentsparamcd paramcd
(teal.transform::choices_selected() dataname.
aval_var
+aval_var
(teal.transform::choices_selected()
subgroup_var
+subgroup_var
(teal.transform::choices_selected()
strata_var
+strata_var
(teal.transform::choices_selected()
stats
-(character)
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Forest Survival Plot — tm_g_forest_tte • teal.modules.clinical teal Module: Forest Survival Plot — tm_g_forest_tte • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Forest Survival Plot
-
Usage
+
Usage
tm_g_forest_tte ( label ,
dataname ,
@@ -85,28 +123,35 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
arm_ref_comp
+arm_ref_comp
(list) optional,ADSL and the element must be another list (possibly
with delayed teal.transform::variable_choices() teal.transform::value_choices()
Argumentssubgroup_var subgroup_var
(teal.transform::choices_selected()
paramcd
+paramcd
(teal.transform::choices_selected() dataname.
strata_var
+strata_var
(teal.transform::choices_selected()
aval_var
+aval_var
(teal.transform::choices_selected()
cnsr_var
+cnsr_var
(teal.transform::choices_selected()
stats
-(character)
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Individual Patient Plots — tm_g_ipp • teal.modules.clinical teal Module: Individual Patient Plots — tm_g_ipp • teal.modules.clinical
+Skip to contents
@@ -17,24 +33,45 @@
+
+
@@ -53,7 +90,8 @@ teal Module: Individual Patient Plots
-
Usage
+
Usage
tm_g_ipp ( label ,
dataname ,
@@ -87,146 +125,184 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected()
paramcd
+paramcd
(teal.transform::choices_selected() dataname.
id_var
+id_var
(teal.transform::choices_selected()
visit_var
+visit_var
(teal.transform::choices_selected() visit variable.
Must be a factor in dataname.
aval_var
+aval_var
(teal.transform::choices_selected()
avalu_var
+avalu_var
(teal.transform::choices_selected()
base_var
+base_var
baseline_var argument instead.
baseline_var
+baseline_var
(teal.transform::choices_selected() baseline_var.
add_baseline_hline
+add_baseline_hline
(logical)
separate_by_obs
+separate_by_obs
(logical)
suppress_legend
+suppress_legend
(logical)
add_avalu
+add_avalu
(logical)avalu_first text should be appended to the plot title and y-axis label.
plot_height
+plot_height
(numeric) optionalc(value, min, max). Specifies the
height of the main plot and renders a slider on the plot to interactively adjust the plot height.
plot_width
+plot_width
(numeric) optionalc(value, min, max). Specifies the width
of the main plot and renders a slider on the plot to interactively adjust the plot width.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
ggplot2_args
-(ggplot2_args) optionalteal.widgets::ggplot2_args()
ggplot2_args
+
+(ggplot2_args) optionalteal.widgets::ggplot2_args() ggplot2_args object with labs list of
the following child elements: title, subtitle, x, y. No other elements are taken into account. The
argument is merged with option teal.ggplot2_args and with default module arguments (hard coded in the module
body).
-For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+
-decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Kaplan-Meier Plot — tm_g_km • teal.modules.clinical teal Module: Kaplan-Meier Plot — tm_g_km • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Kaplan-Meier Plot
-
Usage
+
Usage
tm_g_km ( label ,
dataname ,
@@ -84,28 +122,35 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
arm_ref_comp
+arm_ref_comp
(list) optional,ADSL and the element must be another list (possibly
with delayed teal.transform::variable_choices() teal.transform::value_choices()
Argumentsparamcd paramcd
(teal.transform::choices_selected() dataname.
strata_var
+strata_var
(teal.transform::choices_selected()
facet_var
+facet_var
(teal.transform::choices_selected()
time_unit_var
+time_unit_var
(teal.transform::choices_selected()
aval_var
+aval_var
(teal.transform::choices_selected()
cnsr_var
+cnsr_var
(teal.transform::choices_selected()
conf_level
+conf_level
(teal.transform::choices_selected()
font_size
+font_size
(numeric)
control_annot_surv_med
+control_annot_surv_med
(list)annot_surv_med = TRUE, specified using the control_surv_med_annot() x, y, w, h, and fill. See control_surv_med_annot()
control_annot_coxph
+control_annot_coxph
(list)annot_coxph = TRUE, specified using the control_coxph_annot() x, y, w, h, fill, and ref_lbls. See control_coxph_annot()
legend_pos
+legend_pos
(numeric(2) or NULL)NULL (default), the legend is positioned in the bottom right corner of
the plot, or the middle right of the plot if needed to prevent overlapping.
rel_height_plot
+rel_height_plot
(proportion)1 - rel_height_plot. If annot_at_risk = FALSE or
as_list = TRUE, this parameter is ignored.
plot_height
+plot_height
(numeric) optionalc(value, min, max). Specifies the
height of the main plot and renders a slider on the plot to interactively adjust the plot height.
plot_width
+plot_width
(numeric) optionalc(value, min, max). Specifies the width
of the main plot and renders a slider on the plot to interactively adjust the plot width.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Line Plot — tm_g_lineplot • teal.modules.clinical teal Module: Line Plot — tm_g_lineplot • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Line Plot
-
Usage
+
Usage
tm_g_lineplot ( label ,
dataname ,
@@ -88,162 +126,203 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
strata
+strata
group_var argument instead.
group_var
+group_var
(string or NA)
x
+x
(string)
y
+y
(string)
y_unit
+y_unit
(string or NA)
paramcd
+paramcd
(teal.transform::choices_selected() dataname.
param
+param
(character)
conf_level
+conf_level
(teal.transform::choices_selected()
interval
+interval
(character or NULL)interval variable must be present in the object returned by sfun,
and be of a double or numeric type vector of length two. Set interval = NULL if intervals should not be
added to the plot.
mid
+mid
(character or NULL)mid variable must be present in the object returned by sfun,
and be of a double or numeric type vector of length one.
whiskers
+whiskers
(character)interval that will be returned by sfun (e.g. mean_ci_lwr element of
sfun(x)[["mean_ci"]]). It is possible to specify one whisker only, or to suppress all whiskers by setting
interval = NULL.
table
+table
(character or NULL)table variable must be present in the object returned by sfun.
mid_type
+mid_type
(string)mid plot, it can be point ("p"), line ("l"),
or point and line ("pl").
mid_point_size
+mid_point_size
(numeric(1))mid plot points.
table_font_size
+table_font_size
(numeric(1))
plot_height
+plot_height
(numeric) optionalc(value, min, max). Specifies the
height of the main plot and renders a slider on the plot to interactively adjust the plot height.
plot_width
+plot_width
(numeric) optionalc(value, min, max). Specifies the width
of the main plot and renders a slider on the plot to interactively adjust the plot width.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
ggplot2_args
-(ggplot2_args) optionalteal.widgets::ggplot2_args()
ggplot2_args
+
+(ggplot2_args) optionalteal.widgets::ggplot2_args() ggplot2_args object with labs list of
following child elements: title, subtitle, caption, y, lty. No other elements would be taken into
account. The argument is merged with option teal.ggplot2_args and with default module arguments (hard coded in
the module body).
-For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
+
-decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events • teal.modules.clinical teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Patient Profile Adverse Events Table and Plot
-
Usage
+
Usage
tm_g_pp_adverse_events ( label ,
dataname = "ADAE" ,
@@ -74,139 +112,175 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
patient_col
+patient_col
(character)
aeterm
+aeterm
(teal.transform::choices_selected() AETERM variable from dataname.
tox_grade
+tox_grade
(teal.transform::choices_selected() AETOXGR variable from dataname.
causality
+causality
(teal.transform::choices_selected() AEREL variable from dataname.
outcome
+outcome
(teal.transform::choices_selected() AEOUT variable from dataname.
action
+action
(teal.transform::choices_selected() AEACN variable from dataname.
time
+time
(teal.transform::choices_selected() ASTDY variable from dataname.
decod
+decod
(teal.transform::choices_selected() AEDECOD variable from dataname.
font_size
+font_size
(numeric)
plot_height
+plot_height
(numeric) optionalc(value, min, max). Specifies the
height of the main plot and renders a slider on the plot to interactively adjust the plot height.
plot_width
+plot_width
(numeric) optionalc(value, min, max). Specifies the width
of the main plot and renders a slider on the plot to interactively adjust the plot width.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() teal.ggplot2_args and with default module arguments
(hard coded in the module body).
For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Modules
+
Decorating Modules
-
This module generates the following objects, which can be modified in place using decorators::
plot (ggplot2)
This module generates the following objects, which can be modified in place using decorators::
+Decorators can be applied to all outputs or only to specific objects using a
+
+
Decorators can be applied to all outputs or only to specific objects using a
named list of teal_transform_module objects.
The "default" name is reserved for decorators that are applied to all outputs.
See code snippet below:
-
tm_g_pp_adverse_events (
+
+
tm_g_pp_adverse_events (# arguments for module decorators = list (default = list (teal_transform_module (...)), # applied to all outputs plot = list (teal_transform_module (...)), # applied only to `plot` output table = list (teal_transform_module (...)) # applied only to `table` output
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline • teal.modules.clinical teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Patient Profile Timeline Plot
-
Usage
+
Usage
tm_g_pp_patient_timeline ( label ,
dataname_adcm = "ADCM" ,
@@ -78,145 +116,181 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname_adcm
+dataname_adcm
(character)ADCM dataset or equivalent.
dataname_adae
+dataname_adae
(character)ADAE dataset or equivalent.
parentname
+parentname
(character)ADSL.
patient_col
+patient_col
(character)
aeterm
+aeterm
(teal.transform::choices_selected() AETERM variable from dataname.
cmdecod
+cmdecod
(teal.transform::choices_selected() CMDECOD variable from dataname_adcm.
aetime_start
+aetime_start
(teal.transform::choices_selected() ASTDTM variable from dataname_adae.
aetime_end
+aetime_end
(teal.transform::choices_selected() AENDTM variable from dataname_adae.
dstime_start
+dstime_start
(teal.transform::choices_selected() CMASTDTM variable from dataname_adcm.
dstime_end
+dstime_end
(teal.transform::choices_selected() CMAENDTM variable from dataname_adcm.
aerelday_start
+aerelday_start
(teal.transform::choices_selected() ASTDY variable from dataname_adae.
aerelday_end
+aerelday_end
(teal.transform::choices_selected() AENDY variable from dataname_adae.
dsrelday_start
+dsrelday_start
(teal.transform::choices_selected() ASTDY variable from dataname_adcm.
dsrelday_end
+dsrelday_end
(teal.transform::choices_selected() AENDY variable from dataname_adcm.
font_size
+font_size
(numeric)
plot_height
+plot_height
(numeric) optionalc(value, min, max). Specifies the
height of the main plot and renders a slider on the plot to interactively adjust the plot height.
plot_width
+plot_width
(numeric) optionalc(value, min, max). Specifies the width
of the main plot and renders a slider on the plot to interactively adjust the plot width.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() teal.ggplot2_args and with default module arguments
(hard coded in the module body).
For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy • teal.modules.clinical teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Patient Profile Therapy Table and Plot
-
Usage
+
Usage
tm_g_pp_therapy ( label ,
dataname = "ADCM" ,
@@ -77,154 +115,193 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
patient_col
+patient_col
(character)
atirel
+atirel
(teal.transform::choices_selected() ATIREL variable from dataname.
cmdecod
+cmdecod
(teal.transform::choices_selected() CMDECOD variable from dataname.
cmindc
+cmindc
(teal.transform::choices_selected() CMINDC variable from dataname.
cmdose
+cmdose
(teal.transform::choices_selected() CMDOSE variable from dataname.
cmtrt
+cmtrt
(teal.transform::choices_selected() CMTRT variable from dataname.
cmdosu
+cmdosu
(teal.transform::choices_selected() CMDOSU variable from dataname.
cmroute
+cmroute
(teal.transform::choices_selected() CMROUTE variable from dataname.
cmdosfrq
+cmdosfrq
(teal.transform::choices_selected() CMDOSFRQ variable from dataname.
cmstdy
+cmstdy
(teal.transform::choices_selected() CMSTDY variable from dataname.
cmendy
+cmendy
(teal.transform::choices_selected() CMENDY variable from dataname.
font_size
+font_size
(numeric)
plot_height
+plot_height
(numeric) optionalc(value, min, max). Specifies the
height of the main plot and renders a slider on the plot to interactively adjust the plot height.
plot_width
+plot_width
(numeric) optionalc(value, min, max). Specifies the width
of the main plot and renders a slider on the plot to interactively adjust the plot width.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() teal.ggplot2_args and with default module arguments
(hard coded in the module body).
For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators::
plot (ggplot2)
This module generates the following objects, which can be modified in place using decorators::
+Decorators can be applied to all outputs or only to specific objects using a
+
+
Decorators can be applied to all outputs or only to specific objects using a
named list of teal_transform_module objects.
The "default" name is reserved for decorators that are applied to all outputs.
See code snippet below:
-
tm_g_pp_therapy (
+
+
tm_g_pp_therapy (# arguments for module decorators = list (default = list (teal_transform_module (...)), # applied to all outputs plot = list (teal_transform_module (...)), # applied only to `plot` output table = list (teal_transform_module (...)) # applied only to `table` output
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals • teal.modules.clinical teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Patient Profile Vitals Plot
-
Usage
+
Usage
tm_g_pp_vitals ( label ,
dataname = "ADVS" ,
@@ -71,115 +109,145 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
patient_col
+patient_col
(character)
paramcd
+paramcd
(teal.transform::choices_selected() dataname.
aval
+aval
aval_var argument instead.
aval_var
+aval_var
(teal.transform::choices_selected()
xaxis
+xaxis
(teal.transform::choices_selected() dataname to be put on the plot x-axis.
font_size
+font_size
(numeric)
plot_height
+plot_height
(numeric) optionalc(value, min, max). Specifies the
height of the main plot and renders a slider on the plot to interactively adjust the plot height.
plot_width
+plot_width
(numeric) optionalc(value, min, max). Specifies the width
of the main plot and renders a slider on the plot to interactively adjust the plot width.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
ggplot2_args
+ggplot2_args
(ggplot2_args) optionalteal.widgets::ggplot2_args() teal.ggplot2_args and with default module arguments
(hard coded in the module body).
For more details, see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Details
+
Details
This plot supports horizontal lines for the following 6 PARAMCD levels when they are present in dataname:
"SYSBP", "DIABP", "TEMP", "RESP", "OXYSAT".
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Abnormality Summary Table — tm_t_abnormality • teal.modules.clinical teal Module: Abnormality Summary Table — tm_t_abnormality • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Abnormality Summary Table
-
Usage
+
Usage
tm_t_abnormality ( label ,
dataname ,
@@ -82,149 +120,185 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
by_vars
+by_vars
(teal.transform::choices_selected()
grade
+grade
(teal.transform::choices_selected()
abnormal
+abnormal
(named list)
id_var
+id_var
(teal.transform::choices_selected()
baseline_var
+baseline_var
(teal.transform::choices_selected()
treatment_flag_var
+treatment_flag_var
(teal.transform::choices_selected()
treatment_flag
+treatment_flag
(teal.transform::choices_selected() treatment_flag_var.
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
exclude_base_abn
+exclude_base_abn
(logical)
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
na_level
+na_level
(character)"<Missing>".
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Note
+
Note
Patients with the same abnormality at baseline as on the treatment visit can be
excluded in accordance with GDSR specifications by using exclude_base_abn.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade • teal.modules.clinical teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Laboratory test results with highest grade post-baseline
-
Usage
+
Usage
tm_t_abnormality_by_worst_grade ( label ,
dataname ,
@@ -81,133 +119,165 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
id_var
+id_var
(teal.transform::choices_selected()
paramcd
+paramcd
(teal.transform::choices_selected() dataname.
atoxgr_var
+atoxgr_var
(teal.transform::choices_selected()
worst_high_flag_var
+worst_high_flag_var
(teal.transform::choices_selected()
worst_low_flag_var
+worst_low_flag_var
(teal.transform::choices_selected()
worst_flag_indicator
+worst_flag_indicator
(teal.transform::choices_selected()
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: ANCOVA Summary — tm_t_ancova • teal.modules.clinical teal Module: ANCOVA Summary — tm_t_ancova • teal.modules.clinical
+Skip to contents
@@ -19,24 +35,45 @@
+
+
@@ -56,7 +93,8 @@ teal Module: ANCOVA Summary
-
Usage
+
Usage
tm_t_ancova ( label ,
dataname ,
@@ -81,28 +119,35 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
arm_ref_comp
+arm_ref_comp
(list) optional,ADSL and the element must be another list (possibly
with delayed teal.transform::variable_choices() teal.transform::value_choices()
Argumentsaval_var aval_var
(teal.transform::choices_selected()
cov_var
+cov_var
(teal.transform::choices_selected()
include_interact
+include_interact
(logical)
interact_var
+interact_var
(character)NULL.
interact_y
+interact_y
(character)ANCOVA results when interact_var is discrete. If the interaction is not
needed, the default option is FALSE.
avisit
+avisit
(teal.transform::choices_selected() AVISIT of interest.
paramcd
+paramcd
(teal.transform::choices_selected() dataname.
conf_level
+conf_level
(teal.transform::choices_selected()
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Details
+
Details
When a single endpoint is selected, both unadjusted and adjusted comparison are provided. This modules
-expects that the analysis data has the following variables:
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
data <- teal_data ( ) data <- within ( data , { ADSL <- tmc_ex_adsl
+
+
teal Module: Binary Outcome Table — tm_t_binary_outcome • teal.modules.clinical teal Module: Binary Outcome Table — tm_t_binary_outcome • teal.modules.clinical
+Skip to contents
@@ -17,24 +33,45 @@
+
+
@@ -53,7 +90,8 @@ teal Module: Binary Outcome Table
-
Usage
+
Usage
tm_t_binary_outcome ( label ,
dataname ,
@@ -86,28 +124,35 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
arm_ref_comp
+arm_ref_comp
(list) optional,ADSL and the element must be another list (possibly
with delayed teal.transform::variable_choices() teal.transform::value_choices()
Argumentsparamcd paramcd
(teal.transform::choices_selected() dataname.
strata_var
+strata_var
(teal.transform::choices_selected()
aval_var
+aval_var
(teal.transform::choices_selected()
conf_level
+conf_level
(teal.transform::choices_selected()
default_responses
+default_responses
(list or character)paramcd.
A passed vector is transmitted for all paramcd values. A passed list must be named
@@ -144,12 +194,17 @@
Argumentsrsp_table rsp_table
(logical)RSPT01. Defaults to FALSE.
control
-(named list)
+add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Cox Regression Model — tm_t_coxreg • teal.modules.clinical teal Module: Cox Regression Model — tm_t_coxreg • teal.modules.clinical
+Skip to contents
@@ -21,24 +37,45 @@
+
+
@@ -59,7 +96,8 @@ teal Module: Cox Regression Model
-
Usage
+
Usage
tm_t_coxreg ( label ,
dataname ,
@@ -86,28 +124,35 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
arm_ref_comp
+arm_ref_comp
(list) optional,ADSL and the element must be another list (possibly
with delayed teal.transform::variable_choices() teal.transform::value_choices()
Argumentsparamcd paramcd
(teal.transform::choices_selected() dataname.
cov_var
+cov_var
(teal.transform::choices_selected()
strata_var
+strata_var
(teal.transform::choices_selected()
aval_var
+aval_var
(teal.transform::choices_selected()
cnsr_var
+cnsr_var
(teal.transform::choices_selected()
multivariate
+multivariate
(logical)FALSE, the univariable approach is used instead of the
multi-variable model.
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
conf_level
+conf_level
(teal.transform::choices_selected()
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Details
+
Details
The Cox Proportional Hazards (PH) model is the most commonly used method to
estimate the magnitude of the effect in survival analysis. It assumes proportional
hazards: the ratio of the hazards between groups (e.g., two arms) is constant over time.
This ratio is referred to as the "hazard ratio" (HR) and is one of the most
commonly reported metrics to describe the effect size in survival analysis.
-
This modules expects that the analysis data has the following variables:
AVAL: time to event
This modules expects that the analysis data has the following variables:
+
+AVAL: time to event
CNSR: 1 if record in AVAL is censored, 0 otherwise
PARAMCD: variable used to filter for endpoint (e.g. OS). After
filtering for PARAMCD one observation per patient is expected
The arm variables and stratification/covariate variables are taken from the ADSL data.
+
+
The arm variables and stratification/covariate variables are taken from the ADSL data.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
Examples in Shinylive
-
Examples
+
Examples
## First example ## ============= ## The example below is based on the usual approach involving creation of
+
+
teal Module: Events by Term — tm_t_events • teal.modules.clinical teal Module: Events by Term — tm_t_events • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Events by Term
-
Usage
+
Usage
tm_t_events ( label ,
dataname ,
@@ -77,22 +115,28 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable(s) in the results table.
@@ -100,125 +144,154 @@
Argumentshlt hlt
(teal.transform::choices_selected()
llt
+llt
(teal.transform::choices_selected()
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
event_type
+event_type
(character)"event".
sort_criteria
+sort_criteria
(character)freq_desc sorts
on column sort_freq_col by decreasing number of patients with event. Alternative option alpha sorts events
alphabetically.
sort_freq_col
+sort_freq_col
(character)sort_criteria is set to freq_desc.
prune_freq
+prune_freq
(number)
prune_diff
+prune_diff
(number)
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
incl_overall_sum
+incl_overall_sum
(flag)
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
data <- teal_data ( ) data <- within ( data , { ADSL <- tmc_ex_adsl
+
+
teal Module: Events by Grade — tm_t_events_by_grade • teal.modules.clinical teal Module: Events by Grade — tm_t_events_by_grade • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Events by Grade
-
Usage
+
Usage
tm_t_events_by_grade ( label ,
dataname ,
@@ -77,138 +115,172 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
hlt
+hlt
(teal.transform::choices_selected()
llt
+llt
(teal.transform::choices_selected()
grade
+grade
(character)
grading_groups
+grading_groups
(list)col_by_grade = TRUE.
col_by_grade
+col_by_grade
(logical)
prune_freq
+prune_freq
(number)
prune_diff
+prune_diff
(number)
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear • teal.modules.clinical teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Event Rates Adjusted for Patient-Years
-
Usage
+
Usage
tm_t_events_patyear ( label ,
dataname ,
@@ -77,22 +115,28 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable(s) in the results table.
@@ -100,102 +144,126 @@
Argumentsevents_var events_var
(teal.transform::choices_selected()
paramcd
+paramcd
(teal.transform::choices_selected() dataname.
aval_var
+aval_var
(teal.transform::choices_selected()
avalu_var
+avalu_var
(teal.transform::choices_selected()
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
conf_level
+conf_level
(teal.transform::choices_selected()
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
Examples in Shinylive
-
Examples
+
Examples
+
+
teal Module: Adverse Events Summary — tm_t_events_summary • teal.modules.clinical teal Module: Adverse Events Summary — tm_t_events_summary • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Adverse Events Summary
-
Usage
+
Usage
tm_t_events_summary ( label ,
dataname ,
@@ -85,22 +123,28 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable(s) in the results table.
@@ -108,138 +152,169 @@
Argumentsflag_var_anl flag_var_anl
(teal.transform::choices_selected() NULL)dataset used to count adverse event sub-groups (e.g. Serious events,
Related events, etc.). Variable labels are used as table row names if they exist.
flag_var_aesi
+flag_var_aesi
(teal.transform::choices_selected() NULL)dataset used to count adverse event special interest groups. All flag
variables must be of type logical. Variable labels are used as table row names if they exist.
dthfl_var
+dthfl_var
(teal.transform::choices_selected()
dcsreas_var
+dcsreas_var
(teal.transform::choices_selected() "ADVERSE EVENTS" are summarized in the table row for
"Total number of patients withdrawn from study due to an AE".
llt
+llt
(teal.transform::choices_selected()
aeseq_var
+aeseq_var
(teal.transform::choices_selected() dataset. Used for counting total number of events.
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
count_dth
+count_dth
(logical)dthfl_var). Defaults to TRUE.
count_wd
+count_wd
(logical)dcsreas_var). Defaults to TRUE.
count_subj
+count_subj
(logical)USUBJID). Only applies if
event flag variables are provided.
count_pt
+count_pt
(logical)llt). Only applies if
event flag variables are provided.
count_events
+count_events
(logical)aeseq_var). Only applies if event
flag variables are provided.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Exposure Table for Risk management plan — tm_t_exposure • teal.modules.clinical teal Module: Exposure Table for Risk management plan — tm_t_exposure • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Exposure Table for Risk management plan
-
Usage
+
Usage
tm_t_exposure ( label ,
dataname ,
@@ -81,147 +119,182 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
row_by_var
+row_by_var
(teal.transform::choices_selected()
col_by_var
+col_by_var
(teal.transform::choices_selected()
paramcd
+paramcd
(teal.transform::choices_selected() dataname.
paramcd_label
+paramcd_label
(character)paramcd.
id_var
+id_var
(teal.transform::choices_selected()
parcat
+parcat
(teal.transform::choices_selected()
aval_var
+aval_var
(teal.transform::choices_selected()
avalu_var
+avalu_var
(teal.transform::choices_selected()
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
add_total_row
+add_total_row
(flag)total_row_label argument.
total_row_label
+total_row_label
(character)add_total_row).
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Modules
+
Decorating Modules
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Logistic Regression — tm_t_logistic • teal.modules.clinical teal Module: Logistic Regression — tm_t_logistic • teal.modules.clinical
+Skip to contents
@@ -17,24 +33,45 @@
+
+
@@ -53,7 +90,8 @@ teal Module: Logistic Regression
-
Usage
+
Usage
tm_t_logistic ( label ,
dataname ,
@@ -75,22 +113,28 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() NULL)arm_var. This defines
the grouping variable(s) in the results table. If there are two elements selected for arm_var, the second
@@ -98,7 +142,8 @@
Argumentsarm_ref_comp arm_ref_comp
(list) optional,ADSL and the element must be another list (possibly
with delayed teal.transform::variable_choices() teal.transform::value_choices()
Argumentsparamcd paramcd
(teal.transform::choices_selected() dataname.
cov_var
+cov_var
(teal.transform::choices_selected()
avalc_var
+avalc_var
(teal.transform::choices_selected()
conf_level
+conf_level
(teal.transform::choices_selected()
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Multiple Events by Term — tm_t_mult_events • teal.modules.clinical teal Module: Multiple Events by Term — tm_t_mult_events • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Multiple Events by Term
-
Usage
+
Usage
tm_t_mult_events ( label ,
dataname ,
@@ -73,128 +111,159 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
seq_var
+seq_var
(teal.transform::choices_selected()
hlt
+hlt
(teal.transform::choices_selected()
llt
+llt
(teal.transform::choices_selected()
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
event_type
+event_type
(character)"event".
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
data <- teal_data ( ) data <- within ( data , { ADSL <- tmc_ex_adsl
+
+
teal Module: Patient Profile Basic Info — tm_t_pp_basic_info • teal.modules.clinical teal Module: Patient Profile Basic Info — tm_t_pp_basic_info • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Patient Profile Basic Info
-
Usage
+
Usage
tm_t_pp_basic_info ( label ,
dataname = "ADSL" ,
@@ -63,71 +101,92 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
patient_col
+patient_col
(character)
vars
+vars
(teal.transform::choices_selected() dataname to show in the table.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
data <- teal_data ( ) data <- within ( data , { ADSL <- tmc_ex_adsl
+
+
teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory • teal.modules.clinical teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Patient Profile Laboratory Table
-
Usage
+
Usage
tm_t_pp_laboratory ( label ,
dataname = "ADLB" ,
@@ -71,109 +109,138 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
patient_col
+patient_col
(character)
timepoints
+timepoints
(teal.transform::choices_selected() dataname.
aval
+aval
aval_var argument instead.
aval_var
+aval_var
(teal.transform::choices_selected()
avalu
+avalu
avalu_var argument instead.
avalu_var
+avalu_var
(teal.transform::choices_selected()
param
+param
(teal.transform::choices_selected() PARAM variable from dataname.
paramcd
+paramcd
(teal.transform::choices_selected() dataname.
anrind
+anrind
(teal.transform::choices_selected() ANRIND variable from dataname. Variable should have the
following 3 levels: "HIGH", "LOW", and "NORMAL".
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
data <- teal_data ( ) data <- within ( data , { ADSL <- tmc_ex_adsl
+
+
teal Module: Patient Profile Medical History — tm_t_pp_medical_history • teal.modules.clinical teal Module: Patient Profile Medical History — tm_t_pp_medical_history • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Patient Profile Medical History
-
Usage
+
Usage
tm_t_pp_medical_history ( label ,
dataname = "ADMH" ,
@@ -66,85 +104,109 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
patient_col
+patient_col
(character)
mhterm
+mhterm
(teal.transform::choices_selected() MHTERM variable from dataname.
mhbodsys
+mhbodsys
(teal.transform::choices_selected() MHBODSYS variable from dataname.
mhdistat
+mhdistat
(teal.transform::choices_selected() MHDISTAT variable from dataname.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
data <- teal_data ( ) data <- within ( data , { ADSL <- tmc_ex_adsl
+
+
teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication • teal.modules.clinical teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Patient Profile Prior Medication
-
Usage
+
Usage
tm_t_pp_prior_medication ( label ,
dataname = "ADCM" ,
@@ -67,90 +105,115 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
patient_col
+patient_col
(character)
atirel
+atirel
(teal.transform::choices_selected() ATIREL variable from dataname.
cmdecod
+cmdecod
(teal.transform::choices_selected() CMDECOD variable from dataname.
cmindc
+cmindc
(teal.transform::choices_selected() CMINDC variable from dataname.
cmstdy
+cmstdy
(teal.transform::choices_selected() CMSTDY variable from dataname.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
+
+
teal Module: Shift by Arm — tm_t_shift_by_arm • teal.modules.clinical teal Module: Shift by Arm — tm_t_shift_by_arm • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Shift by Arm
-
Usage
+
Usage
tm_t_shift_by_arm ( label ,
dataname ,
@@ -78,139 +116,173 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
paramcd
+paramcd
(teal.transform::choices_selected() dataname.
visit_var
+visit_var
(teal.transform::choices_selected() visit variable.
Must be a factor in dataname.
aval_var
+aval_var
(teal.transform::choices_selected()
base_var
+base_var
baseline_var argument instead.
baseline_var
+baseline_var
(teal.transform::choices_selected() baseline_var.
treatment_flag_var
+treatment_flag_var
(teal.transform::choices_selected()
treatment_flag
+treatment_flag
(teal.transform::choices_selected() treatment_flag_var.
useNA
+useNA
(character)NA) should be displayed as a level.
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
data <- teal_data ( ) data <- within ( data , { ADSL <- tmc_ex_adsl
+
+
teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst • teal.modules.clinical teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Shift by Arm by Worst Analysis Indicator Level
-
Usage
+
Usage
tm_t_shift_by_arm_by_worst ( label ,
dataname ,
@@ -78,137 +116,171 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
paramcd
+paramcd
(teal.transform::choices_selected() dataname.
aval_var
+aval_var
(teal.transform::choices_selected()
base_var
+base_var
baseline_var argument instead.
baseline_var
+baseline_var
(teal.transform::choices_selected() baseline_var.
worst_flag_var
+worst_flag_var
(teal.transform::choices_selected()
worst_flag
+worst_flag
(character)
treatment_flag_var
+treatment_flag_var
(teal.transform::choices_selected()
treatment_flag
+treatment_flag
(teal.transform::choices_selected() treatment_flag_var.
useNA
+useNA
(character)NA) should be displayed as a level.
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
data <- teal_data ( ) data <- within ( data , { ADSL <- tmc_ex_adsl
+
+
teal Module: Grade Summary Table — tm_t_shift_by_grade • teal.modules.clinical teal Module: Grade Summary Table — tm_t_shift_by_grade • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Grade Summary Table
-
Usage
+
Usage
tm_t_shift_by_grade ( label ,
dataname ,
@@ -87,147 +125,182 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
visit_var
+visit_var
(teal.transform::choices_selected() visit variable.
Must be a factor in dataname.
paramcd
+paramcd
(teal.transform::choices_selected() dataname.
worst_flag_var
+worst_flag_var
(teal.transform::choices_selected()
worst_flag_indicator
+worst_flag_indicator
(teal.transform::choices_selected()
anl_toxgrade_var
+anl_toxgrade_var
(teal.transform::choices_selected()
base_toxgrade_var
+base_toxgrade_var
(teal.transform::choices_selected()
id_var
+id_var
(teal.transform::choices_selected()
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
code_missing_baseline
+code_missing_baseline
(logical)
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+See section "Decorating Module" below for more details.
+
-
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
data <- teal_data ( ) data <- within ( data , { ADSL <- tmc_ex_adsl
+
+
teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq • teal.modules.clinical teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Adverse Events Table by Standardized MedDRA Query
-
Usage
+
Usage
tm_t_smq ( label ,
dataname ,
@@ -76,22 +114,28 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable(s) in the results table.
@@ -99,116 +143,143 @@
Argumentsid_var id_var
(teal.transform::choices_selected()
llt
+llt
(teal.transform::choices_selected()
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
sort_criteria
+sort_criteria
(character)freq_desc sorts
on column sort_freq_col by decreasing number of patients with event. Alternative option alpha sorts events
alphabetically.
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
smq_varlabel
+smq_varlabel
(character)SMQ created by tern::h_stack_by_baskets()
baskets
+baskets
(teal.transform::choices_selected()
scopes
+scopes
(teal.transform::choices_selected()
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
data <- teal_data ( ) data <- within ( data , { ADSL <- tmc_ex_adsl
+
+
teal Module: Summary of Variables — tm_t_summary • teal.modules.clinical teal Module: Summary of Variables — tm_t_summary • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Summary of Variables
-
Usage
+
Usage
tm_t_summary ( label ,
dataname ,
@@ -75,22 +113,28 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable(s) in the results table.
@@ -98,111 +142,137 @@
Argumentssummarize_vars summarize_vars
(teal.transform::choices_selected()
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
show_arm_var_labels
+show_arm_var_labels
(flag)TRUE.
useNA
+useNA
(character)NA) should be displayed as a level.
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
numeric_stats
+numeric_stats
(character)n, mean_sd, mean_ci, median, median_ci, quantiles, range, and geom_mean.
denominator
+denominator
(character)N, the reference
population from the column total is used as the denominator. With option n, the number of non-missing
records in this row and column intersection is used as the denominator. If omit is chosen, then the
percentage is omitted.
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
# Preparation of the test case - use `EOSDY` and `DCSREAS` variables to demonstrate missing data. data <- teal_data ( ) data <- within ( data , {
+
+
teal Module: Summarize Variables by Row Groups — tm_t_summary_by • teal.modules.clinical teal Module: Summarize Variables by Row Groups — tm_t_summary_by • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ teal Module: Summarize Variables by Row Groups
-
Usage
+
Usage
tm_t_summary_by ( label ,
dataname ,
@@ -81,22 +119,28 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable(s) in the results table.
@@ -104,135 +148,166 @@
Argumentsby_vars by_vars
(teal.transform::choices_selected()
summarize_vars
+summarize_vars
(teal.transform::choices_selected()
id_var
+id_var
(teal.transform::choices_selected()
paramcd
+paramcd
(teal.transform::choices_selected() dataname.
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
parallel_vars
+parallel_vars
(logical)TRUE if all chosen analysis variables are numeric.
row_groups
+row_groups
(logical)
useNA
+useNA
(character)NA) should be displayed as a level.
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
numeric_stats
+numeric_stats
(character)n, mean_sd, mean_ci, median, median_ci, quantiles, range, and geom_mean.
denominator
+denominator
(character)N, the reference
population from the column total is used as the denominator. With option n, the number of non-missing
records in this row and column intersection is used as the denominator. If omit is chosen, then the
percentage is omitted.
drop_arm_levels
+drop_arm_levels
(logical)arm_var. If TRUE, arm_var levels are
set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the
parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and
user input for this parameter is ignored.
drop_zero_levels
+drop_zero_levels
(logical)
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
data <- teal_data ( ) data <- within ( data , { ADSL <- tmc_ex_adsl
+
+
teal Module: Time-To-Event Table — tm_t_tte • teal.modules.clinical teal Module: Time-To-Event Table — tm_t_tte • teal.modules.clinical
+Skip to contents
@@ -17,24 +33,45 @@
+
+
@@ -53,7 +90,8 @@ teal Module: Time-To-Event Table
-
Usage
+
Usage
tm_t_tte ( label ,
dataname ,
@@ -87,28 +125,35 @@ Usage
-
Arguments
+
Arguments
-
label
+
+label
(character)
dataname
+dataname
(character)
parentname
+parentname
(character)ADSL.
arm_var
+arm_var
(teal.transform::choices_selected() arm_var.
It defines the grouping variable in the results table.
arm_ref_comp
+arm_ref_comp
(list) optional,ADSL and the element must be another list (possibly
with delayed teal.transform::variable_choices() teal.transform::value_choices()
Argumentsparamcd paramcd
(teal.transform::choices_selected() dataname.
strata_var
+strata_var
(teal.transform::choices_selected()
aval_var
+aval_var
(teal.transform::choices_selected()
cnsr_var
+cnsr_var
(teal.transform::choices_selected()
conf_level_coxph
+conf_level_coxph
(teal.transform::choices_selected()
conf_level_survfit
+conf_level_survfit
(teal.transform::choices_selected()
time_points
+time_points
(teal.transform::choices_selected() tern::surv_timepoint()
time_unit_var
+time_unit_var
(teal.transform::choices_selected()
event_desc_var
+event_desc_var
(character or teal.transform::data_extract_spec()
add_total
+add_total
(logical)
total_label
+total_label
(string)add_total). Defaults to "All Patients". To set a new default total_label to
apply in all modules, run set_default_total_label("new_default").
na_level
+na_level
(string)NA or empty values
in character or factor variables in the data. Defaults to "<Missing>". To set a
default na_level to apply in all modules, run set_default_na_str("new_default").
pre_output
+pre_output
(shiny.tag) optional,
post_output
+post_output
(shiny.tag) optional,shiny::helpText()
basic_table_args
+basic_table_args
(basic_table_args) optionalteal.widgets::basic_table_args() teal.basic_table_args and with default
module arguments (hard coded in the module body).
For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets")
decorators
-
decorators
+
+list of teal_transform_module, named list of teal_transform_module or" NULL) optional,
if not NULL, decorator for tables or plots included in the module.
When a named list of teal_transform_module, the decorators are applied to the respective output objects.
Otherwise, the decorators are applied to all objects, which is equivalent as using the name default.
-See section "Decorating Module" below for more details.
+ See section "Decorating Module" below for more details.
+
+
+
-
Value
+
Value
a teal_module object.
-
Decorating Module
+
Decorating Module
-
This module generates the following objects, which can be modified in place using decorators:
For additional details and examples of decorators, refer to the vignette
+
This module generates the following objects, which can be modified in place using decorators:
+
+
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal") or the teal_transform_module() documentation.
-
See also
+
See also
The TLG Catalog where additional example
apps implementing this module can be found.
-
Examples in Shinylive
+
Examples in Shinylive
-
example-1
+
+example-1
Open in Shinylive
-
Examples
+
Examples
data <- teal_data ( ) data <- within ( data , { ADSL <- tmc_ex_adsl
+
+
Check if vector is valid as to be used as a treatment arm variable — validate_arm • teal.modules.clinical Check if vector is valid as to be used as a treatment arm variable — validate_arm • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,36 +87,44 @@ Check if vector is valid as to be used as a treatment arm variable
-
Arguments
+
Arguments
-
arm_vec
+
+arm_vec
vector to be validated
-
Details
+
Details
A validate error is returned if the vector is not a factor with a more detailed
error message if any of the entries are empty strings
Validate standard input values for a teal module — validate_standard_inputs • teal.modules.clinical Validate standard input values for a teal module — validate_standard_inputs • teal.modules.clinical
+Skip to contents
@@ -15,24 +31,45 @@
+
+
@@ -50,7 +87,8 @@ Validate standard input values for a teal module
-
Usage
+
Usage
validate_standard_inputs ( adsl ,
adslvars = character ( 0 ) ,
@@ -67,69 +105,85 @@ Usage
-
Arguments
+
Arguments
-
adsl
+
+adsl
data.frame with subject-level data
adslvars
+adslvars
required variables from ADSL
anl
+anl
data.frame with analysis data
anlvars
+anlvars
required variables from ANL
need_arm
+need_arm
flag indicating whether grouping variable arm_var
is required or can be optionally NULL.
arm_var
+arm_var
character with name of grouping variable, typically arm
ref_arm
+ref_arm
character with name of reference level in arm_var
comp_arm
+comp_arm
character with name for comparison level in arm_var
min_n_levels_armvar
+min_n_levels_armvar
minimum number of levels in grouping variable arm_var.
Defaults to 1, NULL for no minimum.
max_n_levels_armvar
+max_n_levels_armvar
maximum number of levels in grouping variable arm_var.
Use NULL for no maximum.
min_nrow
+min_nrow
minimum number of observations in ADSL and ANL
+
+
_. Please use underscore (_) delimiter word separation. example, 420_fix_ui_bug suitable branch name change resolving UI-related bug reported issue number 420 current project. change affects multiple repositories, please name branches follows: __. example, 69_awesomeproject_fix_spelling_error reference issue 69 reported project awesomeproject aims resolve one spelling errors multiple (likely related) repositories.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/CONTRIBUTING.html","id":"monorepo-and-stageddependencies","dir":"","previous_headings":"Pull requests","what":"monorepo and staged.dependencies","title":"Contribution Guidelines","text":"Sometimes might need change upstream dependent package(s) able submit meaningful change. using staged.dependencies functionality simulate monorepo behavior. dependency configuration already specified project’s staged_dependencies.yaml file. need name feature branches appropriately. exception branch naming convention described . Please refer staged.dependencies package documentation details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/CONTRIBUTING.html","id":"coding-guidelines","dir":"","previous_headings":"","what":"Coding guidelines","title":"Contribution Guidelines","text":"repository follows unified processes standards adopted maintainers ensure software development carried consistently within teams cohesively across repositories.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/CONTRIBUTING.html","id":"style-guide","dir":"","previous_headings":"Coding guidelines","what":"Style guide","title":"Contribution Guidelines","text":"repository follows standard tidyverse style guide uses lintr lint checks. Customized lint configurations available repository’s .lintr file.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/CONTRIBUTING.html","id":"dependency-management","dir":"","previous_headings":"Coding guidelines","what":"Dependency management","title":"Contribution Guidelines","text":"Lightweight right weight. repository follows tinyverse recommedations limiting dependencies minimum.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/CONTRIBUTING.html","id":"dependency-version-management","dir":"","previous_headings":"Coding guidelines","what":"Dependency version management","title":"Contribution Guidelines","text":"code compatible (!) historical versions given dependenct package, required specify minimal version DESCRIPTION file. particular: development version requires (imports) development version another package - required put abc (>= 1.2.3.9000).","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/CONTRIBUTING.html","id":"r--package-versions","dir":"","previous_headings":"Coding guidelines > Recommended development environment & tools","what":"R & package versions","title":"Contribution Guidelines","text":"continuously test packages newest R version along recent dependencies CRAN BioConductor. recommend working environment also set way. can find details R version packages used R CMD check GitHub Action execution log - step prints R sessionInfo(). discover bugs older R versions older set dependencies, please create relevant bug reports.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/CONTRIBUTING.html","id":"pre-commit","dir":"","previous_headings":"Coding guidelines > Recommended development environment & tools","what":"pre-commit","title":"Contribution Guidelines","text":"highly recommend use pre-commit tool combined R hooks pre-commit execute checks committing pushing changes. Pre-commit hooks already available repository’s .pre-commit-config.yaml file.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/CONTRIBUTING.html","id":"recognition-model","dir":"","previous_headings":"","what":"Recognition model","title":"Contribution Guidelines","text":"mentioned previously, contributions deeply valued appreciated. contribution data available part repository insights, recognize significant contribution hence add contributor package authors list, following rules enforced: Minimum 5% lines code authored* (determined git blame query) top 5 contributors terms number commits lines added lines removed* *Excluding auto-generated code, including limited roxygen comments renv.lock files. package maintainer also reserves right adjust criteria recognize contributions.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/CONTRIBUTING.html","id":"questions","dir":"","previous_headings":"","what":"Questions","title":"Contribution Guidelines","text":"questions regarding contribution guidelines, please contact package/repository maintainer.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/SECURITY.html","id":"reporting-security-issues","dir":"","previous_headings":"","what":"Reporting Security Issues","title":"Security Policy","text":"believe found security vulnerability repositories organization, please report us coordinated disclosure. Please report security vulnerabilities public GitHub issues, discussions, pull requests. Instead, please send email vulnerability.management[@]roche.com. Please include much information listed can help us better understand resolve issue: type issue (e.g., buffer overflow, SQL injection, cross-site scripting) Full paths source file(s) related manifestation issue location affected source code (tag/branch/commit direct URL) special configuration required reproduce issue Step--step instructions reproduce issue Proof--concept exploit code (possible) Impact issue, including attacker might exploit issue information help us triage report quickly.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/SECURITY.html","id":"data-security-standards-dss","dir":"","previous_headings":"","what":"Data Security Standards (DSS)","title":"Security Policy","text":"Please make sure reporting issues form bug, feature, pull request, sensitive information PII, PHI, PCI completely removed text attachments, including pictures videos.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"generating-minimal-data-to-test-teal-modules-clinical","dir":"Articles","previous_headings":"","what":"Generating minimal data to test teal.modules.clinical","title":"Example Data Generation","text":"following script used create save cached synthetic CDISC data data/ directory use examples tests teal.modules.clinical package. script/vignette initialized Emily de la Rua tern. Disclaimer: vignette concerns mainly development minimal stable test data kept internal feature tracking.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"setup-helper-functions","dir":"Articles","previous_headings":"","what":"Setup & Helper Functions","title":"Example Data Generation","text":"","code":"library(dplyr) library(teal.data) study_duration_secs <- lubridate::seconds(lubridate::years(2)) sample_fct <- function(x, N, ...) { checkmate::assert_number(N) factor(sample(x, N, replace = TRUE, ...), levels = if (is.factor(x)) levels(x) else x) } retain <- function(df, value_var, event, outside = NA) { indices <- c(1, which(event == TRUE), nrow(df) + 1) values <- c(outside, value_var[event == TRUE]) rep(values, diff(indices)) } relvar_init <- function(relvar1, relvar2) { if (length(relvar1) != length(relvar2)) { message(simpleError( \"The argument value length of relvar1 and relvar2 differ. They must contain the same number of elements.\" )) return(NA) } return(list(\"relvar1\" = relvar1, \"relvar2\" = relvar2)) } rel_var <- function(df = NULL, var_name = NULL, var_values = NULL, related_var = NULL) { if (is.null(df)) { message(\"Missing data frame argument value.\") return(NA) } else { n_relvar1 <- length(unique(df[, related_var, drop = TRUE])) n_relvar2 <- length(var_values) if (n_relvar1 != n_relvar2) { message(paste(\"Unequal vector lengths for\", related_var, \"and\", var_name)) return(NA) } else { relvar1 <- unique(df[, related_var, drop = TRUE]) relvar2_values <- rep(NA, nrow(df)) for (r in seq_len(length(relvar1))) { matched <- which(df[, related_var, drop = TRUE] == relvar1[r]) relvar2_values[matched] <- var_values[r] } return(relvar2_values) } } } visit_schedule <- function(visit_format = \"WEEK\", n_assessments = 10L, n_days = 5L) { if (!(toupper(visit_format) %in% c(\"WEEK\", \"CYCLE\"))) { message(\"Visit format value must either be: WEEK or CYCLE\") return(NA) } if (toupper(visit_format) == \"WEEK\") { assessments <- 1:n_assessments assessments_ord <- -1:n_assessments visit_values <- c(\"SCREENING\", \"BASELINE\", paste(toupper(visit_format), assessments, \"DAY\", (assessments * 7) + 1)) } else if (toupper(visit_format) == \"CYCLE\") { cycles <- sort(rep(1:n_assessments, times = 1, each = n_days)) days <- rep(seq(1:n_days), times = n_assessments, each = 1) assessments_ord <- 0:(n_assessments * n_days) visit_values <- c(\"SCREENING\", paste(toupper(visit_format), cycles, \"DAY\", days)) } visit_values <- stats::reorder(factor(visit_values), assessments_ord) } rtpois <- function(n, lambda) stats::qpois(stats::runif(n, stats::dpois(0, lambda), 1), lambda) rtexp <- function(n, rate, l = NULL, r = NULL) { if (!is.null(l)) { l - log(1 - stats::runif(n)) / rate } else if (!is.null(r)) { -log(1 - stats::runif(n) * (1 - exp(-r * rate))) / rate } else { stats::rexp(n, rate) } } str_extract <- function(string, pattern) regmatches(string, gregexpr(pattern, string)) with_label <- function(x, label) { attr(x, \"label\") <- as.vector(label) x } common_var_labels <- c( USUBJID = \"Unique Subject Identifier\", STUDYID = \"Study Identifier\", PARAM = \"Parameter\", PARAMCD = \"Parameter Code\", AVISIT = \"Analysis Visit\", AVISITN = \"Analysis Visit (N)\", AVAL = \"Analysis Value\", AVALU = \"Analysis Value Unit\", AVALC = \"Character Result/Finding\", BASE = \"Baseline Value\", BASE2 = \"Screening Value\", ABLFL = \"Baseline Record Flag\", ABLFL2 = \"Screening Record Flag\", CHG = \"Absolute Change from Baseline\", PCHG = \"Percentage Change from Baseline\", ANRIND = \"Analysis Reference Range Indicator\", BNRIND = \"Baseline Reference Range Indicator\", ANRLO = \"Analysis Normal Range Lower Limit\", ANRHI = \"Analysis Normal Range Upper Limit\", CNSR = \"Censor\", ADTM = \"Analysis Datetime\", ADY = \"Analysis Relative Day\", ASTDY = \"Analysis Start Relative Day\", AENDY = \"Analysis End Relative Day\", ASTDTM = \"Analysis Start Datetime\", AENDTM = \"Analysis End Datetime\", VISITDY = \"Planned Study Day of Visit\", EVNTDESC = \"Event or Censoring Description\", CNSDTDSC = \"Censor Date Description\", BASETYPE = \"Baseline Type\", DTYPE = \"Derivation Type\", ONTRTFL = \"On Treatment Record Flag\", WORS01FL = \"Worst Observation in Window Flag 01\", WORS02FL = \"Worst Post-Baseline Observation\" )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"adsl","dir":"Articles","previous_headings":"","what":"ADSL","title":"Example Data Generation","text":"","code":"generate_adsl <- function(N = 200) { set.seed(1) sys_dtm <- lubridate::fast_strptime(\"20/2/2019 11:16:16.683\", \"%d/%m/%Y %H:%M:%OS\", tz = \"UTC\") country_site_prob <- c(.5, .121, .077, .077, .075, .052, .046, .025, .014, .003) adsl <- tibble::tibble( STUDYID = rep(\"AB12345\", N) %>% with_label(\"Study Identifier\"), COUNTRY = sample_fct( c(\"CHN\", \"USA\", \"BRA\", \"PAK\", \"NGA\", \"RUS\", \"JPN\", \"GBR\", \"CAN\", \"CHE\"), N, prob = country_site_prob ) %>% with_label(\"Country\"), SITEID = sample_fct(1:20, N, prob = rep(country_site_prob, times = 2)), SUBJID = paste(\"id\", seq_len(N), sep = \"-\") %>% with_label(\"Subject Identifier for the Study\"), AGE = (sapply(stats::rchisq(N, df = 5, ncp = 10), max, 0) + 20) %>% with_label(\"Age\"), SEX = c(\"F\", \"M\") %>% sample_fct(N, prob = c(.52, .48)) %>% with_label(\"Sex\"), ARMCD = c(\"ARM A\", \"ARM B\", \"ARM C\") %>% sample_fct(N) %>% with_label(\"Planned Arm Code\"), ARM = dplyr::recode( .data$ARMCD, \"ARM A\" = \"A: Drug X\", \"ARM B\" = \"B: Placebo\", \"ARM C\" = \"C: Combination\" ) %>% with_label(\"Description of Planned Arm\"), ACTARMCD = .data$ARMCD %>% with_label(\"Actual Arm Code\"), ACTARM = .data$ARM %>% with_label(\"Description of Actual Arm\"), RACE = c( \"ASIAN\", \"BLACK OR AFRICAN AMERICAN\", \"WHITE\", \"AMERICAN INDIAN OR ALASKA NATIVE\", \"MULTIPLE\", \"NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER\", \"OTHER\", \"UNKNOWN\" ) %>% sample_fct(N, prob = c(.55, .23, .16, .05, .004, .003, .002, .002)) %>% with_label(\"Race\"), TRTSDTM = sys_dtm + sample(seq(0, study_duration_secs), size = N, replace = TRUE) %>% with_label(\"Datetime of First Exposure to Treatment\"), TRTEDTM = c(TRTSDTM + study_duration_secs) %>% with_label(\"Datetime of Last Exposure to Treatment\"), EOSDY = ceiling(as.numeric(difftime(TRTEDTM, TRTSDTM, units = \"days\"))) %>% with_label(\"End of Study Relative Day\"), EOSDT = lubridate::date(TRTEDTM) %>% with_label(\"End of Study Date\"), STRATA1 = c(\"A\", \"B\", \"C\") %>% sample_fct(N) %>% with_label(\"Stratification Factor 1\"), STRATA2 = c(\"S1\", \"S2\") %>% sample_fct(N) %>% with_label(\"Stratification Factor 2\"), BMRKR1 = stats::rchisq(N, 6) %>% with_label(\"Continuous Level Biomarker 1\"), BMRKR2 = sample_fct(c(\"LOW\", \"MEDIUM\", \"HIGH\"), N) %>% with_label(\"Continuous Level Biomarker 2\") ) # associate sites with countries and regions adsl <- adsl %>% dplyr::mutate( SITEID = paste0(.data$COUNTRY, \"-\", .data$SITEID) %>% with_label(\"Study Site Identifier\"), REGION1 = factor(dplyr::case_when( COUNTRY %in% c(\"NGA\") ~ \"Africa\", COUNTRY %in% c(\"CHN\", \"JPN\", \"PAK\") ~ \"Asia\", COUNTRY %in% c(\"RUS\") ~ \"Eurasia\", COUNTRY %in% c(\"GBR\") ~ \"Europe\", COUNTRY %in% c(\"CAN\", \"USA\") ~ \"North America\", COUNTRY %in% c(\"BRA\") ~ \"South America\", TRUE ~ as.character(NA) )) %>% with_label(\"Geographic Region 1\"), SAFFL = factor(\"Y\") %>% with_label(\"Safety Population Flag\") ) %>% dplyr::mutate( USUBJID = paste(.data$STUDYID, .data$SITEID, .data$SUBJID, sep = \"-\") %>% with_label(\"Unique Subject Identifier\") ) # disposition related variables # using probability of 1 for the \"DEATH\" level to ensure at least one death record exists l_dcsreas <- list( choices = c( \"ADVERSE EVENT\", \"DEATH\", \"LACK OF EFFICACY\", \"PHYSICIAN DECISION\", \"PROTOCOL VIOLATION\", \"WITHDRAWAL BY PARENT/GUARDIAN\", \"WITHDRAWAL BY SUBJECT\" ), prob = c(.2, 1, .1, .1, .2, .1, .1) ) l_dthcat_other <- list( choices = c( \"Post-study reporting of death\", \"LOST TO FOLLOW UP\", \"MISSING\", \"SUICIDE\", \"UNKNOWN\" ), prob = c(.1, .3, .3, .2, .1) ) adsl <- adsl %>% dplyr::mutate( EOSSTT = dplyr::case_when( EOSDY == max(EOSDY, na.rm = TRUE) ~ \"COMPLETED\", EOSDY < max(EOSDY, na.rm = TRUE) ~ \"DISCONTINUED\", is.na(TRTEDTM) ~ \"ONGOING\" ) %>% with_label(\"End of Study Status\") ) %>% dplyr::mutate( EOTSTT = .data$EOSSTT %>% with_label(\"End of Treatment Status\") ) %>% dplyr::mutate( DCSREAS = ifelse( .data$EOSSTT == \"DISCONTINUED\", sample(x = l_dcsreas$choices, size = N, replace = TRUE, prob = l_dcsreas$prob), as.character(NA) ) %>% with_label(\"Reason for Discontinuation from Study\") ) tmc_ex_adsl <- adsl %>% dplyr::mutate(DTHDT = dplyr::case_when( DCSREAS == \"DEATH\" ~ lubridate::date(TRTEDTM + lubridate::days(sample(0:50, size = N, replace = TRUE))) ) %>% with_label(\"Date of Death\")) save(tmc_ex_adsl, file = \"data/tmc_ex_adsl.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"adae","dir":"Articles","previous_headings":"","what":"ADAE","title":"Example Data Generation","text":"","code":"generate_adae <- function(adsl = tmc_ex_adsl, max_n_aes = 5) { set.seed(1) lookup_ae <- tibble::tribble( ~AEBODSYS, ~AELLT, ~AEDECOD, ~AEHLT, ~AEHLGT, ~AETOXGR, ~AESOC, ~AESER, ~AEREL, \"cl A.1\", \"llt A.1.1.1.1\", \"dcd A.1.1.1.1\", \"hlt A.1.1.1\", \"hlgt A.1.1\", \"1\", \"cl A\", \"N\", \"N\", \"cl A.1\", \"llt A.1.1.1.2\", \"dcd A.1.1.1.2\", \"hlt A.1.1.1\", \"hlgt A.1.1\", \"2\", \"cl A\", \"Y\", \"N\", \"cl B.1\", \"llt B.1.1.1.1\", \"dcd B.1.1.1.1\", \"hlt B.1.1.1\", \"hlgt B.1.1\", \"5\", \"cl B\", \"Y\", \"Y\", \"cl B.2\", \"llt B.2.1.2.1\", \"dcd B.2.1.2.1\", \"hlt B.2.1.2\", \"hlgt B.2.1\", \"3\", \"cl B\", \"N\", \"N\", \"cl B.2\", \"llt B.2.2.3.1\", \"dcd B.2.2.3.1\", \"hlt B.2.2.3\", \"hlgt B.2.2\", \"1\", \"cl B\", \"Y\", \"N\", \"cl C.1\", \"llt C.1.1.1.3\", \"dcd C.1.1.1.3\", \"hlt C.1.1.1\", \"hlgt C.1.1\", \"4\", \"cl C\", \"N\", \"Y\", \"cl C.2\", \"llt C.2.1.2.1\", \"dcd C.2.1.2.1\", \"hlt C.2.1.2\", \"hlgt C.2.1\", \"2\", \"cl C\", \"N\", \"Y\", \"cl D.1\", \"llt D.1.1.1.1\", \"dcd D.1.1.1.1\", \"hlt D.1.1.1\", \"hlgt D.1.1\", \"5\", \"cl D\", \"Y\", \"Y\", \"cl D.1\", \"llt D.1.1.4.2\", \"dcd D.1.1.4.2\", \"hlt D.1.1.4\", \"hlgt D.1.1\", \"3\", \"cl D\", \"N\", \"N\", \"cl D.2\", \"llt D.2.1.5.3\", \"dcd D.2.1.5.3\", \"hlt D.2.1.5\", \"hlgt D.2.1\", \"1\", \"cl D\", \"N\", \"Y\" ) aag <- utils::read.table( sep = \",\", header = TRUE, text = paste( \"NAMVAR,SRCVAR,GRPTYPE,REFNAME,REFTERM,SCOPE\", \"CQ01NAM,AEDECOD,CUSTOM,D.2.1.5.3/A.1.1.1.1 aesi,dcd D.2.1.5.3,\", \"CQ01NAM,AEDECOD,CUSTOM,D.2.1.5.3/A.1.1.1.1 aesi,dcd A.1.1.1.1,\", \"SMQ01NAM,AEDECOD,SMQ,C.1.1.1.3/B.2.2.3.1 aesi,dcd C.1.1.1.3,BROAD\", \"SMQ01NAM,AEDECOD,SMQ,C.1.1.1.3/B.2.2.3.1 aesi,dcd B.2.2.3.1,BROAD\", \"SMQ02NAM,AEDECOD,SMQ,Y.9.9.9.9/Z.9.9.9.9 aesi,dcd Y.9.9.9.9,NARROW\", \"SMQ02NAM,AEDECOD,SMQ,Y.9.9.9.9/Z.9.9.9.9 aesi,dcd Z.9.9.9.9,NARROW\", sep = \"\\n\" ), stringsAsFactors = FALSE ) adae <- Map( function(id, sid) { n_aes <- sample(c(0, seq_len(max_n_aes)), 1) i <- sample(seq_len(nrow(lookup_ae)), n_aes, TRUE) dplyr::mutate( lookup_ae[i, ], USUBJID = id, STUDYID = sid ) }, adsl$USUBJID, adsl$STUDYID ) %>% Reduce(rbind, .) %>% `[`(c(10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9)) %>% dplyr::mutate( AETERM = gsub(\"dcd\", \"trm\", .data$AEDECOD) %>% with_label(\"Reported Term for the Adverse Event\"), AESEV = dplyr::case_when( AETOXGR == 1 ~ \"MILD\", AETOXGR %in% c(2, 3) ~ \"MODERATE\", AETOXGR %in% c(4, 5) ~ \"SEVERE\" ) %>% with_label(\"Severity/Intensity\") ) # merge adsl to be able to add AE date and study day variables adae <- dplyr::inner_join(adae, adsl, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\") %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::mutate(ASTDTM = sample( seq(lubridate::as_datetime(TRTSDTM), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1 )) %>% dplyr::mutate(ASTDY = ceiling(difftime(ASTDTM, TRTSDTM, units = \"days\"))) %>% # add 1 to end of range incase both values passed to sample() are the same dplyr::mutate(AENDTM = sample( seq(lubridate::as_datetime(ASTDTM), lubridate::as_datetime(TRTENDT + 1), by = \"day\"), size = 1 )) %>% dplyr::mutate(AENDY = ceiling(difftime(AENDTM, TRTSDTM, units = \"days\"))) %>% dplyr::mutate(LDOSEDTM = dplyr::case_when( TRTSDTM < ASTDTM ~ lubridate::as_datetime(stats::runif(1, TRTSDTM, ASTDTM)), TRUE ~ ASTDTM )) %>% dplyr::select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ASTDTM, .data$AETERM) adae <- adae %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(AESEQ = seq_len(dplyr::n())) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$ASTDTM, .data$AETERM, .data$AESEQ ) outcomes <- c( \"UNKNOWN\", \"NOT RECOVERED/NOT RESOLVED\", \"RECOVERED/RESOLVED WITH SEQUELAE\", \"RECOVERING/RESOLVING\", \"RECOVERED/RESOLVED\" ) adae <- adae %>% dplyr::mutate( AEOUT = factor(ifelse( .data$AETOXGR == \"5\", \"FATAL\", as.character(sample_fct(outcomes, nrow(adae), prob = c(0.1, 0.2, 0.1, 0.3, 0.3))) )) %>% with_label(\"Outcome of Adverse Event\"), TRTEMFL = ifelse(.data$ASTDTM >= .data$TRTSDTM, \"Y\", \"\") %>% with_label(\"Treatment Emergent Analysis Flag\") ) l_aag <- split(aag, interaction(aag$NAMVAR, aag$SRCVAR, aag$GRPTYPE, drop = TRUE)) # Create aesi flags l_aesi <- lapply(l_aag, function(d_adag, d_adae) { names(d_adag)[names(d_adag) == \"REFTERM\"] <- d_adag$SRCVAR[1] names(d_adag)[names(d_adag) == \"REFNAME\"] <- d_adag$NAMVAR[1] if (d_adag$GRPTYPE[1] == \"CUSTOM\") { d_adag <- d_adag[-which(names(d_adag) == \"SCOPE\")] } else if (d_adag$GRPTYPE[1] == \"SMQ\") { names(d_adag)[names(d_adag) == \"SCOPE\"] <- paste0(substr(d_adag$NAMVAR[1], 1, 5), \"SC\") } d_adag <- d_adag[-which(names(d_adag) %in% c(\"NAMVAR\", \"SRCVAR\", \"GRPTYPE\"))] d_new <- dplyr::left_join(x = d_adae, y = d_adag, by = intersect(names(d_adae), names(d_adag))) d_new[, dplyr::setdiff(names(d_new), names(d_adae)), drop = FALSE] }, adae) adae <- dplyr::bind_cols(adae, l_aesi) actions <- c( \"DOSE RATE REDUCED\", \"UNKNOWN\", \"NOT APPLICABLE\", \"DRUG INTERRUPTED\", \"DRUG WITHDRAWN\", \"DOSE INCREASED\", \"DOSE NOT CHANGED\", \"DOSE REDUCED\", \"NOT EVALUABLE\" ) tmc_ex_adae <- adae %>% dplyr::mutate( AEACN = factor(ifelse( .data$AETOXGR == \"5\", \"NOT EVALUABLE\", as.character(sample_fct(actions, nrow(adae), prob = c(0.05, 0.05, 0.05, 0.01, 0.05, 0.1, 0.45, 0.1, 0.05))) )) %>% with_label(\"Action Taken With Study Treatment\") ) %>% col_relabel( AEBODSYS = \"Body System or Organ Class\", AELLT = \"Lowest Level Term\", AEDECOD = \"Dictionary-Derived Term\", AEHLT = \"High Level Term\", AEHLGT = \"High Level Group Term\", AETOXGR = \"Analysis Toxicity Grade\", AESOC = \"Primary System Organ Class\", AESER = \"Serious Event\", AEREL = \"Analysis Causality\", AESEQ = \"Sponsor-Defined Identifier\", LDOSEDTM = \"End Time/Time of Last Dose\", CQ01NAM = \"CQ 01 Reference Name\", SMQ01NAM = \"SMQ 01 Reference Name\", SMQ01SC = \"SMQ 01 Scope\", SMQ02NAM = \"SMQ 02 Reference Name\", SMQ02SC = \"SMQ 02 Scope\" ) i_lbls <- sapply( names(col_labels(tmc_ex_adae)[is.na(col_labels(tmc_ex_adae))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adae[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adae, file = \"data/tmc_ex_adae.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"adaette","dir":"Articles","previous_headings":"","what":"ADAETTE","title":"Example Data Generation","text":"","code":"generate_adaette <- function(adsl = tmc_ex_adsl) { set.seed(1) lookup_adaette <- tibble::tribble( ~ARM, ~CATCD, ~CAT, ~LAMBDA, ~CNSR_P, \"ARM A\", \"1\", \"any adverse event\", 1 / 80, 0.4, \"ARM B\", \"1\", \"any adverse event\", 1 / 100, 0.2, \"ARM C\", \"1\", \"any adverse event\", 1 / 60, 0.42, \"ARM A\", \"2\", \"any serious adverse event\", 1 / 100, 0.3, \"ARM B\", \"2\", \"any serious adverse event\", 1 / 150, 0.1, \"ARM C\", \"2\", \"any serious adverse event\", 1 / 80, 0.32, \"ARM A\", \"3\", \"a grade 3-5 adverse event\", 1 / 80, 0.2, \"ARM B\", \"3\", \"a grade 3-5 adverse event\", 1 / 100, 0.08, \"ARM C\", \"3\", \"a grade 3-5 adverse event\", 1 / 60, 0.23 ) evntdescr_sel <- \"Preferred Term\" cnsdtdscr_sel <- c( \"Clinical Cut Off\", \"Completion or Discontinuation\", \"End of AE Reporting Period\" ) random_patient_data <- function(patient_info) { startdt <- lubridate::date(patient_info$TRTSDTM) trtedtm <- lubridate::floor_date(dplyr::case_when( is.na(patient_info$TRTEDTM) ~ lubridate::date(patient_info$TRTSDTM) + study_duration_secs, TRUE ~ lubridate::date(patient_info$TRTEDTM) ), unit = \"day\") enddts <- c(patient_info$EOSDT, lubridate::date(trtedtm)) enddts_min_index <- which.min(enddts) adt <- enddts[enddts_min_index] adtm <- lubridate::as_datetime(adt) ady <- as.numeric(adt - startdt + 1) data.frame( ARM = patient_info$ARM, STUDYID = patient_info$STUDYID, SITEID = patient_info$SITEID, USUBJID = patient_info$USUBJID, PARAMCD = \"AEREPTTE\", PARAM = \"Time to end of AE reporting period\", CNSR = 0, AVAL = lubridate::days(ady) / lubridate::years(1), AVALU = \"YEARS\", EVNTDESC = ifelse(enddts_min_index == 1, \"Completion or Discontinuation\", \"End of AE Reporting Period\"), CNSDTDSC = NA, ADTM = adtm, ADY = ady, stringsAsFactors = FALSE ) } paramcd_hy <- c(\"HYSTTEUL\", \"HYSTTEBL\") param_hy <- c(\"Time to Hy's Law Elevation in relation to ULN\", \"Time to Hy's Law Elevation in relation to Baseline\") param_init_list <- relvar_init(param_hy, paramcd_hy) adsl_hy <- dplyr::select(adsl, \"STUDYID\", \"USUBJID\", \"TRTSDTM\", \"SITEID\", \"ARM\") adaette_hy <- expand.grid( STUDYID = unique(adsl$STUDYID), USUBJID = adsl$USUBJID, PARAM = as.factor(param_init_list$relvar1), stringsAsFactors = FALSE ) adaette_hy <- dplyr::left_join(adaette_hy, adsl_hy, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\") %>% dplyr::mutate( PARAMCD = factor(rel_var( df = as.data.frame(adaette_hy), var_values = param_init_list$relvar2, related_var = \"PARAM\" )) ) %>% dplyr::mutate( CNSR = sample(c(0, 1), prob = c(0.1, 0.9), size = dplyr::n(), replace = TRUE), EVNTDESC = dplyr::if_else( .data$CNSR == 0, \"First Post-Baseline Raised ALT or AST Elevation Result\", NA_character_ ), CNSDTDSC = dplyr::if_else(.data$CNSR == 0, NA_character_, sample(c(\"Last Post-Baseline ALT or AST Result\", \"Treatment Start\"), prob = c(0.9, 0.1), size = dplyr::n(), replace = TRUE ) ) ) %>% dplyr::rowwise() %>% dplyr::mutate(ADTM = dplyr::case_when( CNSDTDSC == \"Treatment Start\" ~ TRTSDTM, TRUE ~ TRTSDTM + sample(seq(0, study_duration_secs), size = dplyr::n(), replace = TRUE) )) %>% dplyr::mutate( ADY_int = lubridate::date(ADTM) - lubridate::date(TRTSDTM) + 1, ADY = as.numeric(ADY_int), AVAL = lubridate::days(ADY_int) / lubridate::weeks(1), AVALU = \"WEEKS\" ) %>% dplyr::select(-TRTSDTM, -ADY_int) random_ae_data <- function(lookup_info, patient_info, patient_data) { cnsr <- sample(c(0, 1), 1, prob = c(1 - lookup_info$CNSR_P, lookup_info$CNSR_P)) ae_rep_tte <- patient_data$AVAL[patient_data$PARAMCD == \"AEREPTTE\"] data.frame( ARM = rep(patient_data$ARM, 2), STUDYID = rep(patient_data$STUDYID, 2), SITEID = rep(patient_data$SITEID, 2), USUBJID = rep(patient_data$USUBJID, 2), PARAMCD = c( paste0(\"AETTE\", lookup_info$CATCD), paste0(\"AETOT\", lookup_info$CATCD) ), PARAM = c( paste(\"Time to first occurrence of\", lookup_info$CAT), paste(\"Number of occurrences of\", lookup_info$CAT) ), CNSR = c(cnsr, NA), AVAL = c( ifelse(cnsr == 1, ae_rep_tte, rtexp(1, lookup_info$LAMBDA * 365.25, r = ae_rep_tte)), ifelse(cnsr == 1, 0, rtpois(1, lookup_info$LAMBDA * 365.25)) ), AVALU = c(\"YEARS\", NA), EVNTDESC = c(ifelse(cnsr == 0, sample(evntdescr_sel, 1), \"\"), NA), CNSDTDSC = c(ifelse(cnsr == 1, sample(cnsdtdscr_sel, 1), \"\"), NA), stringsAsFactors = FALSE ) %>% dplyr::mutate( ADY = dplyr::if_else(is.na(AVALU), NA_real_, ceiling(as.numeric(lubridate::dyears(AVAL), \"days\"))), ADTM = dplyr::if_else( is.na(AVALU), lubridate::as_datetime(NA), patient_info$TRTSDTM + lubridate::days(ADY) ) ) } adaette <- split(adsl, adsl$USUBJID) %>% lapply(function(patient_info) { patient_data <- random_patient_data(patient_info) lookup_arm <- lookup_adaette %>% dplyr::filter(.data$ARM == as.character(patient_info$ARMCD)) ae_data <- split(lookup_arm, lookup_arm$CATCD) %>% lapply(random_ae_data, patient_data = patient_data, patient_info = patient_info) %>% Reduce(rbind, .) dplyr::bind_rows(patient_data, ae_data) }) %>% Reduce(rbind, .) adaette <- rbind(adaette, adaette_hy) tmc_ex_adaette <- adsl %>% dplyr::inner_join( dplyr::select(adaette, -\"SITEID\", -\"ARM\"), by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::group_by(.data$USUBJID) %>% dplyr::arrange(.data$ADTM) %>% dplyr::mutate(PARAM = as.factor(.data$PARAM)) %>% dplyr::mutate(PARAMCD = as.factor(.data$PARAMCD)) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$ADTM ) i_lbls <- sapply( names(col_labels(tmc_ex_adaette)[is.na(col_labels(tmc_ex_adaette))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adaette[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adaette, file = \"data/tmc_ex_adaette.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"adcm","dir":"Articles","previous_headings":"","what":"ADCM","title":"Example Data Generation","text":"","code":"generate_adcm <- function(adsl = tmc_ex_adsl, max_n_cms = 5L) { set.seed(1) lookup_cm <- tibble::tribble( ~CMCLAS, ~CMDECOD, ~ATIREL, \"medcl A\", \"medname A_1/3\", \"PRIOR\", \"medcl A\", \"medname A_2/3\", \"CONCOMITANT\", \"medcl A\", \"medname A_3/3\", \"CONCOMITANT\", \"medcl B\", \"medname B_1/4\", \"CONCOMITANT\", \"medcl B\", \"medname B_2/4\", \"PRIOR\", \"medcl B\", \"medname B_3/4\", \"PRIOR\", \"medcl B\", \"medname B_4/4\", \"CONCOMITANT\", \"medcl C\", \"medname C_1/2\", \"CONCOMITANT\", \"medcl C\", \"medname C_2/2\", \"CONCOMITANT\" ) adcm <- Map(function(id, sid) { n_cms <- sample(c(0, seq_len(max_n_cms)), 1) i <- sample(seq_len(nrow(lookup_cm)), n_cms, TRUE) dplyr::mutate( lookup_cm[i, ], USUBJID = id, STUDYID = sid ) }, adsl$USUBJID, adsl$STUDYID) %>% Reduce(rbind, .) %>% `[`(c(4, 5, 1, 2, 3)) %>% dplyr::mutate(CMCAT = .data$CMCLAS %>% with_label(\"Category for Medication\")) # merge adsl to be able to add CM date and study day variables adcm <- dplyr::inner_join( adcm, adsl, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::mutate(ASTDTM = sample( seq(lubridate::as_datetime(TRTSDTM), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1 )) %>% dplyr::mutate(ASTDY = ceiling(difftime(ASTDTM, TRTSDTM, units = \"days\"))) %>% # add 1 to end of range incase both values passed to sample() are the same dplyr::mutate(AENDTM = sample( seq(lubridate::as_datetime(ASTDTM), lubridate::as_datetime(TRTENDT + 1), by = \"day\"), size = 1 )) %>% dplyr::mutate(AENDY = ceiling(difftime(AENDTM, TRTSDTM, units = \"days\"))) %>% dplyr::select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(STUDYID, USUBJID, ASTDTM) tmc_ex_adcm <- adcm %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(CMSEQ = seq_len(dplyr::n())) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ASTDTM, .data$CMSEQ) %>% dplyr::mutate( ATC1 = paste(\"ATCCLAS1\", substr(.data$CMDECOD, 9, 9)) %>% with_label(\"ATC Level 1 Text\"), ATC2 = paste(\"ATCCLAS2\", substr(.data$CMDECOD, 9, 9)) %>% with_label(\"ATC Level 2 Text\"), ATC3 = paste(\"ATCCLAS3\", substr(.data$CMDECOD, 9, 9)) %>% with_label(\"ATC Level 3 Text\"), ATC4 = paste(\"ATCCLAS4\", substr(.data$CMDECOD, 9, 9)) %>% with_label(\"ATC Level 4 Text\") ) %>% dplyr::mutate( CMINDC = sample(c( \"Nausea\", \"Hypertension\", \"Urticaria\", \"Fever\", \"Asthma\", \"Infection\", \"Diabete\", \"Diarrhea\", \"Pneumonia\" ), dplyr::n(), replace = TRUE) %>% with_label(\"Indication\"), CMDOSE = sample(1:99, dplyr::n(), replace = TRUE) %>% with_label(\"Dose per Administration\"), CMTRT = substr(.data$CMDECOD, 9, 13) %>% with_label(\"Reported Name of Drug, Med, or Therapy\"), CMDOSU = sample(c( \"ug/mL\", \"ug/kg/day\", \"%\", \"uL\", \"DROP\", \"umol/L\", \"mg\", \"mg/breath\", \"ug\" ), dplyr::n(), replace = TRUE) %>% with_label(\"Dose Units\") ) %>% dplyr::mutate( CMROUTE = sample(c( \"INTRAVENOUS\", \"ORAL\", \"NASAL\", \"INTRAMUSCULAR\", \"SUBCUTANEOUS\", \"INHALED\", \"RECTAL\", \"UNKNOWN\" ), dplyr::n(), replace = TRUE) %>% with_label(\"Route of Administration\"), CMDOSFRQ = sample(c( \"Q4W\", \"QN\", \"Q4H\", \"UNKNOWN\", \"TWICE\", \"Q4H\", \"QD\", \"TID\", \"4 TIMES PER MONTH\" ), dplyr::n(), replace = TRUE) %>% with_label(\"Dosing Frequency per Interval\") ) %>% col_relabel( CMCLAS = \"Medication Class\", CMDECOD = \"Standardized Medication Name\", ATIREL = \"Time Relation of Medication\", CMSEQ = \"Sponsor-Defined Identifier\" ) i_lbls <- sapply( names(col_labels(tmc_ex_adcm)[is.na(col_labels(tmc_ex_adcm))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adcm[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adcm, file = \"data/tmc_ex_adcm.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"adeg","dir":"Articles","previous_headings":"","what":"ADEG","title":"Example Data Generation","text":"","code":"generate_adeg <- function(adsl = tmc_ex_adsl, n_assessments = 3L, n_days = 3L, max_n_eg = 3L) { set.seed(1) param <- c(\"QT Duration\", \"RR Duration\", \"Heart Rate\", \"ECG Interpretation\") paramcd <- c(\"QT\", \"RR\", \"HR\", \"ECGINTP\") paramu <- c(\"msec\", \"msec\", \"beats/min\", \"\") visit_format <- \"WEEK\" param_init_list <- relvar_init(param, paramcd) unit_init_list <- relvar_init(param, paramu) adeg <- expand.grid( STUDYID = unique(adsl$STUDYID), USUBJID = adsl$USUBJID, PARAM = as.factor(param_init_list$relvar1), AVISIT = visit_schedule(visit_format = visit_format, n_assessments = n_assessments, n_days = n_days), stringsAsFactors = FALSE ) adeg$PARAMCD <- as.factor(rel_var( df = adeg, var_name = \"PARAMCD\", var_values = param_init_list$relvar2, related_var = \"PARAM\" )) adeg <- adeg %>% dplyr::mutate(AVAL = dplyr::case_when( .data$PARAMCD == \"QT\" ~ stats::rnorm(nrow(adeg), mean = 350, sd = 100), .data$PARAMCD == \"RR\" ~ stats::rnorm(nrow(adeg), mean = 1050, sd = 300), .data$PARAMCD == \"HR\" ~ stats::rnorm(nrow(adeg), mean = 70, sd = 20), .data$PARAMCD == \"ECGINTP\" ~ NA_real_ )) adeg <- adeg %>% dplyr::mutate(AVISITN = dplyr::case_when( AVISIT == \"SCREENING\" ~ -1, AVISIT == \"BASELINE\" ~ 0, (grepl(\"^WEEK\", AVISIT) | grepl(\"^CYCLE\", AVISIT)) ~ as.numeric(AVISIT) - 2, TRUE ~ NA_real_ )) adeg$AVALU <- as.factor(rel_var( df = adeg, var_name = \"AVALU\", var_values = unit_init_list$relvar2, related_var = \"PARAM\" )) adeg <- adeg[order(adeg$STUDYID, adeg$USUBJID, adeg$PARAMCD, adeg$AVISITN), ] adeg <- Reduce(rbind, lapply(split(adeg, adeg$USUBJID), function(x) { x$STUDYID <- adsl$STUDYID[which(adsl$USUBJID == x$USUBJID[1])] x$ABLFL <- ifelse(toupper(visit_format) == \"WEEK\" & x$AVISIT == \"BASELINE\", \"Y\", ifelse(toupper(visit_format) == \"CYCLE\" & x$AVISIT == \"CYCLE 1 DAY 1\", \"Y\", \"\") ) x })) adeg$BASE <- ifelse(adeg$AVISITN >= 0, retain(adeg, adeg$AVAL, adeg$ABLFL == \"Y\"), adeg$AVAL) adeg <- adeg %>% dplyr::mutate(ANRLO = dplyr::case_when( .data$PARAMCD == \"QT\" ~ 200, .data$PARAMCD == \"RR\" ~ 600, .data$PARAMCD == \"HR\" ~ 40, .data$PARAMCD == \"ECGINTP\" ~ NA_real_ )) %>% dplyr::mutate(ANRHI = dplyr::case_when( .data$PARAMCD == \"QT\" ~ 500, .data$PARAMCD == \"RR\" ~ 1500, .data$PARAMCD == \"HR\" ~ 100, .data$PARAMCD == \"ECGINTP\" ~ NA_real_ )) %>% dplyr::mutate(ANRIND = factor(dplyr::case_when( .data$AVAL < .data$ANRLO ~ \"LOW\", .data$AVAL >= .data$ANRLO & .data$AVAL <= .data$ANRHI ~ \"NORMAL\", .data$AVAL > .data$ANRHI ~ \"HIGH\" ))) adeg <- adeg %>% dplyr::mutate(CHG = ifelse(.data$AVISITN > 0, .data$AVAL - .data$BASE, NA)) %>% dplyr::mutate(PCHG = ifelse(.data$AVISITN > 0, 100 * (.data$CHG / .data$BASE), NA)) %>% dplyr::mutate(BASETYPE = \"LAST\") %>% dplyr::group_by(.data$USUBJID, .data$PARAMCD, .data$BASETYPE) %>% dplyr::mutate(BNRIND = .data$ANRIND[.data$ABLFL == \"Y\"]) %>% dplyr::ungroup() %>% dplyr::mutate(DTYPE = NA) adeg$ANRIND <- factor(adeg$ANRIND, levels = c(\"LOW\", \"NORMAL\", \"HIGH\")) adeg$BNRIND <- factor(adeg$BNRIND, levels = c(\"LOW\", \"NORMAL\", \"HIGH\")) adeg <- dplyr::inner_join( adsl, adeg, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::ungroup() %>% dplyr::group_by(USUBJID) %>% dplyr::arrange(USUBJID, AVISITN) %>% dplyr::mutate(ADTM = rep( sort(sample( seq(lubridate::as_datetime(TRTSDTM[1]), lubridate::as_datetime(TRTENDT[1]), by = \"day\"), size = nlevels(AVISIT) )), each = n() / nlevels(AVISIT) )) %>% dplyr::ungroup() %>% dplyr::select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ADTM) adeg <- adeg %>% dplyr::group_by(.data$USUBJID) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$BASETYPE, .data$AVISITN, .data$DTYPE, .data$ADTM ) adeg <- adeg %>% dplyr::mutate(ONTRTFL = factor(dplyr::case_when( is.na(.data$TRTSDTM) ~ \"\", is.na(.data$ADTM) ~ \"Y\", (.data$ADTM < .data$TRTSDTM) ~ \"\", (.data$ADTM > .data$TRTEDTM) ~ \"\", TRUE ~ \"Y\" ))) %>% dplyr::mutate(AVALC = ifelse( .data$PARAMCD == \"ECGINTP\", as.character(sample_fct(c(\"ABNORMAL\", \"NORMAL\"), nrow(adeg), prob = c(0.25, 0.75))), as.character(.data$AVAL) )) adeg <- adeg %>% dplyr::mutate(row_check = seq_len(nrow(adeg))) get_groups <- function(data, minimum) { data <- data %>% dplyr::group_by(.data$USUBJID, .data$PARAMCD, .data$BASETYPE) %>% dplyr::arrange(.data$ADTM) %>% dplyr::filter( (.data$AVISIT != \"BASELINE\" & .data$AVISIT != \"SCREENING\") & (.data$ONTRTFL == \"Y\" | .data$ADTM <= .data$TRTSDTM) ) %>% { if (minimum == TRUE) { dplyr::filter(., .data$AVAL == min(.data$AVAL)) %>% dplyr::mutate(., DTYPE = \"MINIMUM\", AVISIT = \"POST-BASELINE MINIMUM\") } else { dplyr::filter(., .data$AVAL == max(.data$AVAL)) %>% dplyr::mutate(., DTYPE = \"MAXIMUM\", AVISIT = \"POST-BASELINE MAXIMUM\") } } %>% dplyr::slice(1) %>% dplyr::ungroup() return(data) } lbls <- col_labels(adeg) adeg <- rbind(adeg, get_groups(adeg, TRUE), get_groups(adeg, FALSE)) %>% dplyr::arrange(.data$row_check) %>% dplyr::group_by(.data$USUBJID, .data$PARAMCD, .data$BASETYPE) %>% dplyr::arrange(.data$AVISIT, .by_group = TRUE) %>% dplyr::ungroup() col_labels(adeg) <- lbls adeg <- adeg[, -which(names(adeg) %in% c(\"row_check\"))] flag_variables <- function(data, worst_obs) { data_compare <- data %>% dplyr::mutate(row_check = seq_len(nrow(data))) data <- data_compare %>% { if (worst_obs == FALSE) { dplyr::group_by(., .data$USUBJID, .data$PARAMCD, .data$BASETYPE, .data$AVISIT) %>% dplyr::arrange(., .data$ADTM) } else { dplyr::group_by(., .data$USUBJID, .data$PARAMCD, .data$BASETYPE) } } %>% dplyr::filter( .data$AVISITN > 0 & (.data$ONTRTFL == \"Y\" | .data$ADTM <= .data$TRTSDTM) & is.na(.data$DTYPE) ) %>% { if (worst_obs == TRUE) { dplyr::arrange(., .data$AVALC) %>% dplyr::filter(., ifelse( .data$PARAMCD == \"ECGINTP\", ifelse(.data$AVALC == \"ABNORMAL\", .data$AVALC == \"ABNORMAL\", .data$AVALC == \"NORMAL\"), .data$AVAL == min(.data$AVAL) )) } else { dplyr::filter(., ifelse( .data$PARAMCD == \"ECGINTP\", .data$AVALC == \"ABNORMAL\" | .data$AVALC == \"NORMAL\", .data$AVAL == min(.data$AVAL) )) } } %>% dplyr::slice(1) %>% { if (worst_obs == TRUE) { dplyr::mutate(., new_var = dplyr::case_when( (.data$AVALC == \"ABNORMAL\" | .data$AVALC == \"NORMAL\") ~ \"Y\", (!is.na(.data$AVAL) & is.na(.data$DTYPE)) ~ \"Y\", TRUE ~ \"\" )) } else { dplyr::mutate(., new_var = dplyr::case_when( (.data$AVALC == \"ABNORMAL\" | .data$AVALC == \"NORMAL\") ~ \"Y\", (!is.na(.data$AVAL) & is.na(.data$DTYPE)) ~ \"Y\", TRUE ~ \"\" )) } } %>% dplyr::ungroup() data_compare$new_var <- ifelse(data_compare$row_check %in% data$row_check, \"Y\", \"\") data_compare <- data_compare[, -which(names(data_compare) %in% c(\"row_check\"))] return(data_compare) } adeg <- flag_variables(adeg, FALSE) %>% dplyr::rename(WORS01FL = \"new_var\") adeg <- flag_variables(adeg, TRUE) %>% dplyr::rename(WORS02FL = \"new_var\") tmc_ex_adeg <- adeg %>% dplyr::group_by(.data$USUBJID, .data$PARAMCD, .data$BASETYPE) %>% dplyr::mutate(BASEC = ifelse( .data$PARAMCD == \"ECGINTP\", .data$AVALC[.data$AVISIT == \"BASELINE\"], as.character(.data$BASE) )) %>% dplyr::ungroup() %>% col_relabel(BASEC = \"Baseline Character Value\") i_lbls <- sapply( names(col_labels(tmc_ex_adeg)[is.na(col_labels(tmc_ex_adeg))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adeg[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adeg, file = \"data/tmc_ex_adeg.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"adex","dir":"Articles","previous_headings":"","what":"ADEX","title":"Example Data Generation","text":"","code":"generate_adex <- function(adsl = tmc_ex_adsl, n_assessments = 3L, n_days = 3L, max_n_exs = 3L) { set.seed(1) param <- c( \"Dose administered during constant dosing interval\", \"Number of doses administered during constant dosing interval\", \"Total dose administered\", \"Total number of doses administered\" ) paramcd <- c(\"DOSE\", \"NDOSE\", \"TDOSE\", \"TNDOSE\") paramu <- c(\"mg\", \" \", \"mg\", \" \") parcat1 <- c(\"INDIVIDUAL\", \"OVERALL\") parcat2 <- c(\"Drug A\", \"Drug B\") visit_format <- \"WEEK\" param_init_list <- relvar_init(param, paramcd) unit_init_list <- relvar_init(param, paramu) adex <- expand.grid( STUDYID = unique(adsl$STUDYID), USUBJID = adsl$USUBJID, PARAM = c( rep( param_init_list$relvar1[1], length(levels(visit_schedule(visit_format = visit_format, n_assessments = n_assessments, n_days = n_days))) ), rep( param_init_list$relvar1[2], length(levels(visit_schedule(visit_format = visit_format, n_assessments = n_assessments, n_days = n_days))) ), param_init_list$relvar1[3:4] ), stringsAsFactors = FALSE ) adex$PARAMCD <- as.factor(rel_var( df = adex, var_name = \"PARAMCD\", var_values = param_init_list$relvar2, related_var = \"PARAM\" )) adex$AVALU <- as.factor(rel_var( df = adex, var_name = \"AVALU\", var_values = unit_init_list$relvar2, related_var = \"PARAM\" )) adex <- adex %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(PARCAT_ind = sample(c(1, 2), size = 1)) %>% dplyr::mutate(PARCAT2 = ifelse(.data$PARCAT_ind == 1, parcat2[1], parcat2[2])) %>% dplyr::select(-\"PARCAT_ind\") adex <- adex %>% dplyr::mutate(PARCAT1 = dplyr::case_when( (.data$PARAMCD == \"TNDOSE\" | .data$PARAMCD == \"TDOSE\") ~ \"OVERALL\", .data$PARAMCD == \"DOSE\" | .data$PARAMCD == \"NDOSE\" ~ \"INDIVIDUAL\" )) adex_visit <- adex %>% dplyr::filter(.data$PARAMCD == \"DOSE\" | .data$PARAMCD == \"NDOSE\") %>% dplyr::mutate( AVISIT = rep(visit_schedule(visit_format = visit_format, n_assessments = n_assessments, n_days = n_days), 2) ) adex <- dplyr::left_join( adex %>% dplyr::group_by( .data$USUBJID, .data$STUDYID, .data$PARAM, .data$PARAMCD, .data$AVALU, .data$PARCAT1, .data$PARCAT2 ) %>% dplyr::mutate(id = dplyr::row_number()), adex_visit %>% dplyr::group_by( .data$USUBJID, .data$STUDYID, .data$PARAM, .data$PARAMCD, .data$AVALU, .data$PARCAT1, .data$PARCAT2 ) %>% dplyr::mutate(id = dplyr::row_number()), by = c(\"USUBJID\", \"STUDYID\", \"PARCAT1\", \"PARCAT2\", \"id\", \"PARAMCD\", \"PARAM\", \"AVALU\") ) %>% dplyr::select(-\"id\") adex <- adex %>% dplyr::mutate(AVISITN = dplyr::case_when( AVISIT == \"SCREENING\" ~ -1, AVISIT == \"BASELINE\" ~ 0, (grepl(\"^WEEK\", AVISIT) | grepl(\"^CYCLE\", AVISIT)) ~ as.numeric(AVISIT) - 2, TRUE ~ 999000 )) adex2 <- split(adex, adex$USUBJID) %>% lapply(function(pinfo) { pinfo %>% dplyr::filter(.data$PARAMCD == \"DOSE\") %>% dplyr::group_by(.data$USUBJID, .data$PARCAT2, .data$AVISIT) %>% dplyr::mutate(changeind = dplyr::case_when( .data$AVISIT == \"SCREENING\" ~ 0, .data$AVISIT != \"SCREENING\" ~ sample(c(-1, 0, 1), size = 1, prob = c(0.25, 0.5, 0.25), replace = TRUE ) )) %>% dplyr::ungroup() %>% dplyr::group_by(.data$USUBJID, .data$PARCAT2) %>% dplyr::mutate( csum = cumsum(.data$changeind), changeind = dplyr::case_when( .data$csum <= -3 ~ sample(c(0, 1), size = 1, prob = c(0.5, 0.5)), .data$csum >= 3 ~ sample(c(0, -1), size = 1, prob = c(0.5, 0.5)), TRUE ~ .data$changeind ) ) %>% dplyr::mutate(csum = cumsum(.data$changeind)) %>% dplyr::ungroup() %>% dplyr::group_by(.data$USUBJID, .data$PARCAT2, .data$AVISIT) %>% dplyr::mutate(AVAL = dplyr::case_when( .data$csum == -2 ~ 480, .data$csum == -1 ~ 720, .data$csum == 0 ~ 960, .data$csum == 1 ~ 1200, .data$csum == 2 ~ 1440 )) %>% dplyr::select(-c(\"csum\", \"changeind\")) %>% dplyr::ungroup() }) %>% Reduce(rbind, .) adextmp <- dplyr::full_join(adex2, adex, by = names(adex)) adex <- adextmp %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(AVAL = ifelse(.data$PARAMCD == \"NDOSE\", 1, .data$AVAL)) %>% dplyr::mutate(AVAL = ifelse( .data$PARAMCD == \"TNDOSE\", sum(.data$AVAL[.data$PARAMCD == \"NDOSE\"]), .data$AVAL )) %>% dplyr::ungroup() %>% dplyr::group_by(.data$USUBJID, .data$STUDYID, .data$PARCAT2) %>% dplyr::mutate(AVAL = ifelse( .data$PARAMCD == \"TDOSE\", sum(.data$AVAL[.data$PARAMCD == \"DOSE\"]), .data$AVAL )) adex <- dplyr::inner_join(adsl, adex, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\") %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::mutate(ASTDTM = sample( seq(lubridate::as_datetime(TRTSDTM), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1 )) %>% dplyr::select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ASTDTM) adex <- adex %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(EXSEQ = seq_len(dplyr::n())) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$ASTDTM, .data$AVISITN ) %>% col_relabel( PARCAT1 = \"Parameter Category (Individual/Overall)\", PARCAT2 = \"Parameter Category (Drug A/Drug B)\", EXSEQ = \"Analysis Sequence Number\" ) visit_levels <- str_extract(levels(adex$AVISIT), pattern = \"[0-9]+\") vl_extracted <- vapply(visit_levels, function(x) as.numeric(x[2]), numeric(1)) vl_extracted <- c(-1, 1, vl_extracted[!is.na(vl_extracted)]) tmc_ex_adex <- adex %>% dplyr::mutate(VISITDY = as.numeric(as.character(factor(AVISIT, labels = vl_extracted)))) %>% dplyr::mutate(ASTDTM = lubridate::as_datetime(TRTSDTM) + lubridate::days(VISITDY)) %>% dplyr::distinct(USUBJID, .keep_all = TRUE) i_lbls <- sapply( names(col_labels(tmc_ex_adex)[is.na(col_labels(tmc_ex_adex))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adex[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adex, file = \"data/tmc_ex_adex.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"adlb","dir":"Articles","previous_headings":"","what":"ADLB","title":"Example Data Generation","text":"","code":"generate_adlb <- function(adsl = tmc_ex_adsl, n_assessments = 3L, n_days = 3L, max_n_lbs = 3L) { set.seed(1) lbcat <- c(\"CHEMISTRY\", \"CHEMISTRY\", \"IMMUNOLOGY\") param <- c( \"Alanine Aminotransferase Measurement\", \"C-Reactive Protein Measurement\", \"Immunoglobulin A Measurement\" ) paramcd <- c(\"ALT\", \"CRP\", \"IGA\") paramu <- c(\"U/L\", \"mg/L\", \"g/L\") aval_mean <- c(20, 1, 2) visit_format <- \"WEEK\" # validate and initialize related variables lbcat_init_list <- relvar_init(param, lbcat) param_init_list <- relvar_init(param, paramcd) unit_init_list <- relvar_init(param, paramu) adlb <- expand.grid( STUDYID = unique(adsl$STUDYID), USUBJID = adsl$USUBJID, PARAM = as.factor(param_init_list$relvar1), AVISIT = visit_schedule(visit_format = visit_format, n_assessments = n_assessments, n_days = n_days), stringsAsFactors = FALSE ) # assign AVAL based on different test adlb <- adlb %>% dplyr::mutate(AVAL = stats::rnorm(nrow(adlb), mean = 1, sd = 0.2)) %>% dplyr::left_join(data.frame(PARAM = param, ADJUST = aval_mean), by = \"PARAM\") %>% dplyr::mutate(AVAL = .data$AVAL * .data$ADJUST) %>% dplyr::select(-\"ADJUST\") # assign related variable values: PARAMxLBCAT are related adlb$LBCAT <- as.factor(rel_var( df = adlb, var_name = \"LBCAT\", var_values = lbcat_init_list$relvar2, related_var = \"PARAM\" )) # assign related variable values: PARAMxPARAMCD are related adlb$PARAMCD <- as.factor(rel_var( df = adlb, var_name = \"PARAMCD\", var_values = param_init_list$relvar2, related_var = \"PARAM\" )) adlb$AVALU <- as.factor(rel_var( df = adlb, var_name = \"AVALU\", var_values = unit_init_list$relvar2, related_var = \"PARAM\" )) adlb <- adlb %>% dplyr::mutate(AVISITN = dplyr::case_when( AVISIT == \"SCREENING\" ~ -1, AVISIT == \"BASELINE\" ~ 0, (grepl(\"^WEEK\", AVISIT) | grepl(\"^CYCLE\", AVISIT)) ~ as.numeric(AVISIT) - 2, TRUE ~ NA_real_ )) adlb <- adlb %>% dplyr::mutate(AVISITN = dplyr::case_when( AVISIT == \"SCREENING\" ~ -1, AVISIT == \"BASELINE\" ~ 0, (grepl(\"^WEEK\", AVISIT) | grepl(\"^CYCLE\", AVISIT)) ~ as.numeric(AVISIT) - 2, TRUE ~ NA_real_ )) # order to prepare for change from screening and baseline values adlb <- adlb[order(adlb$STUDYID, adlb$USUBJID, adlb$PARAMCD, adlb$AVISITN), ] adlb <- Reduce(rbind, lapply(split(adlb, adlb$USUBJID), function(x) { x$STUDYID <- adsl$STUDYID[which(adsl$USUBJID == x$USUBJID[1])] x$ABLFL2 <- ifelse(x$AVISIT == \"SCREENING\", \"Y\", \"\") x$ABLFL <- ifelse(toupper(visit_format) == \"WEEK\" & x$AVISIT == \"BASELINE\", \"Y\", ifelse(toupper(visit_format) == \"CYCLE\" & x$AVISIT == \"CYCLE 1 DAY 1\", \"Y\", \"\") ) x })) adlb$BASE <- ifelse(adlb$ABLFL2 != \"Y\", retain(adlb, adlb$AVAL, adlb$ABLFL == \"Y\"), NA) anrind_choices <- c(\"HIGH\", \"LOW\", \"NORMAL\") adlb <- adlb %>% dplyr::mutate(BASETYPE = \"LAST\") %>% dplyr::mutate(ANRIND = sample_fct(anrind_choices, nrow(adlb), prob = c(0.1, 0.1, 0.8))) %>% dplyr::mutate(ANRLO = dplyr::case_when( .data$PARAMCD == \"ALT\" ~ 7, .data$PARAMCD == \"CRP\" ~ 8, .data$PARAMCD == \"IGA\" ~ 0.8 )) %>% dplyr::mutate(ANRHI = dplyr::case_when( .data$PARAMCD == \"ALT\" ~ 55, .data$PARAMCD == \"CRP\" ~ 10, .data$PARAMCD == \"IGA\" ~ 3 )) %>% dplyr::mutate(DTYPE = NA) %>% dplyr::mutate( ATOXGR = factor(dplyr::case_when( .data$ANRIND == \"LOW\" ~ sample( c(\"-1\", \"-2\", \"-3\", \"-4\", \"-5\"), nrow(adlb), replace = TRUE, prob = c(0.30, 0.25, 0.20, 0.15, 0) ), .data$ANRIND == \"HIGH\" ~ sample( c(\"1\", \"2\", \"3\", \"4\", \"5\"), nrow(adlb), replace = TRUE, prob = c(0.30, 0.25, 0.20, 0.15, 0) ), .data$ANRIND == \"NORMAL\" ~ \"0\" )) %>% with_label(\"Analysis Toxicity Grade\") ) %>% dplyr::group_by(.data$USUBJID, .data$PARAMCD, .data$BASETYPE) %>% dplyr::mutate(BTOXGR = .data$ATOXGR[.data$ABLFL == \"Y\"]) %>% dplyr::ungroup() %>% col_relabel(BTOXGR = \"Baseline Toxicity Grade\") # High and low descriptions of the different PARAMCD values # This is currently hard coded as the GDSR does not have these descriptions yet grade_lookup <- tibble::tribble( ~PARAMCD, ~ATOXDSCL, ~ATOXDSCH, \"ALB\", \"Hypoalbuminemia\", NA_character_, \"ALKPH\", NA_character_, \"Alkaline phosphatase increased\", \"ALT\", NA_character_, \"Alanine aminotransferase increased\", \"AST\", NA_character_, \"Aspartate aminotransferase increased\", \"BILI\", NA_character_, \"Blood bilirubin increased\", \"CA\", \"Hypocalcemia\", \"Hypercalcemia\", \"CHOLES\", NA_character_, \"Cholesterol high\", \"CK\", NA_character_, \"CPK increased\", \"CREAT\", NA_character_, \"Creatinine increased\", \"CRP\", NA_character_, \"C reactive protein increased\", \"GGT\", NA_character_, \"GGT increased\", \"GLUC\", \"Hypoglycemia\", \"Hyperglycemia\", \"HGB\", \"Anemia\", \"Hemoglobin increased\", \"IGA\", NA_character_, \"Immunoglobulin A increased\", \"POTAS\", \"Hypokalemia\", \"Hyperkalemia\", \"LYMPH\", \"CD4 lymphocytes decreased\", NA_character_, \"PHOS\", \"Hypophosphatemia\", NA_character_, \"PLAT\", \"Platelet count decreased\", NA_character_, \"SODIUM\", \"Hyponatremia\", \"Hypernatremia\", \"WBC\", \"White blood cell decreased\", \"Leukocytosis\", ) # merge grade_lookup onto adlb adlb <- dplyr::left_join(adlb, grade_lookup, by = \"PARAMCD\") # merge adsl to be able to add LB date and study day variables adlb <- dplyr::inner_join( adsl, adlb, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::ungroup() %>% dplyr::group_by(USUBJID) %>% dplyr::arrange(USUBJID, AVISITN) %>% dplyr::mutate(ADTM = rep( sort(sample( seq(lubridate::as_datetime(TRTSDTM[1]), lubridate::as_datetime(TRTENDT[1]), by = \"day\"), size = nlevels(AVISIT) )), each = n() / nlevels(AVISIT) )) %>% dplyr::ungroup() %>% dplyr::select(-TRTENDT) %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ADTM) adlb <- adlb %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(LBSEQ = seq_len(dplyr::n())) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$BASETYPE, .data$AVISITN, .data$DTYPE, .data$ADTM, .data$LBSEQ ) %>% col_relabel(LBSEQ = \"Lab Test or Examination Sequence Number\") adlb <- adlb %>% dplyr::mutate(ONTRTFL = factor(dplyr::case_when( is.na(.data$TRTSDTM) ~ \"\", is.na(.data$ADTM) ~ \"Y\", (.data$ADTM < .data$TRTSDTM) ~ \"\", (.data$ADTM > .data$TRTEDTM) ~ \"\", TRUE ~ \"Y\" ))) flag_variables <- function(data, apply_grouping, apply_filter, apply_mutate) { data_compare <- data %>% dplyr::mutate(row_check = seq_len(nrow(data))) data <- data_compare %>% { if (apply_grouping == TRUE) { dplyr::group_by(., .data$USUBJID, .data$PARAMCD, .data$BASETYPE, .data$AVISIT) } else { dplyr::group_by(., .data$USUBJID, .data$PARAMCD, .data$BASETYPE) } } %>% dplyr::arrange(.data$ADTM, .data$LBSEQ) %>% { if (apply_filter == TRUE) { dplyr::filter( ., (.data$AVISIT != \"BASELINE\" & .data$AVISIT != \"SCREENING\") & (.data$ONTRTFL == \"Y\" | .data$ADTM <= .data$TRTSDTM) ) %>% dplyr::filter(.data$ATOXGR == max(as.numeric(as.character(.data$ATOXGR)))) } else if (apply_filter == FALSE) { dplyr::filter( ., (.data$AVISIT != \"BASELINE\" & .data$AVISIT != \"SCREENING\") & (.data$ONTRTFL == \"Y\" | .data$ADTM <= .data$TRTSDTM) ) %>% dplyr::filter(.data$ATOXGR == min(as.numeric(as.character(.data$ATOXGR)))) } else { dplyr::filter( ., .data$AVAL == min(.data$AVAL) & (.data$AVISIT != \"BASELINE\" & .data$AVISIT != \"SCREENING\") & (.data$ONTRTFL == \"Y\" | .data$ADTM <= .data$TRTSDTM) ) } } %>% dplyr::slice(1) %>% { if (apply_mutate == TRUE) { dplyr::mutate(., new_var = ifelse(is.na(.data$DTYPE), \"Y\", \"\")) } else { dplyr::mutate(., new_var = ifelse(is.na(.data$AVAL) == FALSE & is.na(.data$DTYPE), \"Y\", \"\")) } } %>% dplyr::ungroup() data_compare$new_var <- ifelse(data_compare$row_check %in% data$row_check, \"Y\", \"\") data_compare <- data_compare[, -which(names(data_compare) %in% c(\"row_check\"))] return(data_compare) } adlb <- flag_variables(adlb, TRUE, \"ELSE\", FALSE) %>% dplyr::rename(WORS01FL = \"new_var\") adlb <- flag_variables(adlb, FALSE, TRUE, TRUE) %>% dplyr::rename(WGRHIFL = \"new_var\") adlb <- flag_variables(adlb, FALSE, FALSE, TRUE) %>% dplyr::rename(WGRLOFL = \"new_var\") adlb <- flag_variables(adlb, TRUE, TRUE, TRUE) %>% dplyr::rename(WGRHIVFL = \"new_var\") adlb <- flag_variables(adlb, TRUE, FALSE, TRUE) %>% dplyr::rename(WGRLOVFL = \"new_var\") tmc_ex_adlb <- adlb %>% dplyr::mutate( ANL01FL = ifelse( (.data$ABLFL == \"Y\" | (.data$WORS01FL == \"Y\" & is.na(.data$DTYPE))) & (.data$AVISIT != \"SCREENING\"), \"Y\", \"\" ) %>% with_label(\"Analysis Flag 01 Baseline Post-Baseline\"), PARAM = as.factor(.data$PARAM) ) tmc_ex_adlb <- tmc_ex_adlb %>% group_by(.data$USUBJID, .data$PARAMCD, .data$BASETYPE) %>% mutate(BNRIND = .data$ANRIND[.data$ABLFL == \"Y\"]) %>% ungroup() %>% dplyr::mutate(ADY = ceiling(as.numeric(difftime(.data$ADTM, .data$TRTSDTM, units = \"days\")))) tmc_ex_adlb$PARAMCD <- as.factor(tmc_ex_adlb$PARAMCD) tmc_ex_adlb <- tmc_ex_adlb %>% dplyr::mutate(CHG = .data$AVAL - .data$BASE) %>% dplyr::mutate(PCHG = 100 * (.data$CHG / .data$BASE)) %>% col_relabel( LBCAT = \"Category for Lab Test\", ATOXDSCL = \"Analysis Toxicity Description Low\", ATOXDSCH = \"Analysis Toxicity Description High\", WGRHIFL = \"Worst High Grade per Patient\", WGRLOFL = \"Worst Low Grade per Patient\", WGRHIVFL = \"Worst High Grade per Patient per Visit\", WGRLOVFL = \"Worst Low Grade per Patient per Visit\" ) i_lbls <- sapply( names(col_labels(tmc_ex_adlb)[is.na(col_labels(tmc_ex_adlb))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adlb[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adlb, file = \"data/tmc_ex_adlb.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"admh","dir":"Articles","previous_headings":"","what":"ADMH","title":"Example Data Generation","text":"","code":"generate_admh <- function(adsl = tmc_ex_adsl, max_n_mhs = 10L) { set.seed(1) lookup_mh <- tibble::tribble( ~MHBODSYS, ~MHDECOD, ~MHSOC, \"cl A\", \"trm A_1/2\", \"cl A\", \"cl A\", \"trm A_2/2\", \"cl A\", \"cl B\", \"trm B_1/3\", \"cl B\", \"cl B\", \"trm B_2/3\", \"cl B\", \"cl B\", \"trm B_3/3\", \"cl B\", \"cl C\", \"trm C_1/2\", \"cl C\", \"cl C\", \"trm C_2/2\", \"cl C\", \"cl D\", \"trm D_1/3\", \"cl D\", \"cl D\", \"trm D_2/3\", \"cl D\", \"cl D\", \"trm D_3/3\", \"cl D\" ) admh <- Map( function(id, sid) { n_mhs <- sample(0:max_n_mhs, 1) i <- sample(seq_len(nrow(lookup_mh)), n_mhs, TRUE) dplyr::mutate( lookup_mh[i, ], USUBJID = id, STUDYID = sid ) }, adsl$USUBJID, adsl$STUDYID ) %>% Reduce(rbind, .) %>% `[`(c(4, 5, 1, 2, 3)) %>% dplyr::mutate(MHTERM = .data$MHDECOD %>% with_label(\"Reported Term for the Medical History\")) admh <- dplyr::inner_join( adsl, admh, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::mutate(ASTDTM = sample( seq(lubridate::as_datetime(TRTSDTM), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1 )) %>% select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ASTDTM, .data$MHTERM) %>% dplyr::mutate(MHDISTAT = sample( x = c(\"Resolved\", \"Ongoing with treatment\", \"Ongoing without treatment\"), prob = c(0.6, 0.2, 0.2), size = dplyr::n(), replace = TRUE ) %>% with_label(\"Status of Disease\")) tmc_ex_admh <- admh %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(MHSEQ = seq_len(dplyr::n())) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ASTDTM) %>% col_relabel( MHBODSYS = \"Body System or Organ Class\", MHDECOD = \"Dictionary-Derived Term\", MHSOC = \"Primary System Organ Class\", MHSEQ = \"Sponsor-Defined Identifier\" ) i_lbls <- sapply( names(col_labels(tmc_ex_admh)[is.na(col_labels(tmc_ex_admh))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_admh[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_admh, file = \"data/tmc_ex_admh.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"adqs","dir":"Articles","previous_headings":"","what":"ADQS","title":"Example Data Generation","text":"","code":"generate_adqs <- function(adsl = tmc_ex_adsl, n_assessments = 5L, n_days = 5L) { set.seed(1) param <- c( \"BFI All Questions\", \"Fatigue Interference\", \"Function/Well-Being (GF1,GF3,GF7)\", \"Treatment Side Effects (GP2,C5,GP5)\", \"FKSI-19 All Questions\" ) paramcd <- c(\"BFIALL\", \"FATIGI\", \"FKSI-FWB\", \"FKSI-TSE\", \"FKSIALL\") visit_format <- \"WEEK\" param_init_list <- relvar_init(param, paramcd) adqs <- expand.grid( STUDYID = unique(adsl$STUDYID), USUBJID = adsl$USUBJID, PARAM = param_init_list$relvar1, AVISIT = visit_schedule(visit_format = visit_format, n_assessments = n_assessments, n_days = n_days), stringsAsFactors = FALSE ) adqs <- dplyr::mutate( adqs, AVISITN = dplyr::case_when( AVISIT == \"SCREENING\" ~ -1, AVISIT == \"BASELINE\" ~ 0, (grepl(\"^WEEK\", AVISIT) | grepl(\"^CYCLE\", AVISIT)) ~ as.numeric(AVISIT) - 2, TRUE ~ NA_real_ ) ) adqs$PARAMCD <- rel_var(df = adqs, var_name = \"PARAMCD\", var_values = param_init_list$relvar2, related_var = \"PARAM\") adqs$AVAL <- stats::rnorm(nrow(adqs), mean = 50, sd = 8) + adqs$AVISITN * stats::rnorm(nrow(adqs), mean = 5, sd = 2) adqs <- adqs[order(adqs$STUDYID, adqs$USUBJID, adqs$PARAMCD, adqs$AVISITN), ] adqs <- Reduce( rbind, lapply( split(adqs, adqs$USUBJID), function(x) { x$STUDYID <- adsl$STUDYID[which(adsl$USUBJID == x$USUBJID[1])] x$ABLFL2 <- ifelse(x$AVISIT == \"SCREENING\", \"Y\", \"\") x$ABLFL <- ifelse( toupper(visit_format) == \"WEEK\" & x$AVISIT == \"BASELINE\", \"Y\", ifelse( toupper(visit_format) == \"CYCLE\" & x$AVISIT == \"CYCLE 1 DAY 1\", \"Y\", \"\" ) ) x } ) ) adqs$BASE <- ifelse(adqs$ABLFL2 != \"Y\", retain(adqs, adqs$AVAL, adqs$ABLFL == \"Y\"), NA) adqs <- adqs %>% dplyr::mutate(CHG = .data$AVAL - .data$BASE) adqs <- dplyr::inner_join( adsl, adqs, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% ungroup() %>% group_by(USUBJID) %>% arrange(USUBJID, AVISITN) %>% dplyr::mutate(ADTM = rep( sort(sample( seq(lubridate::as_datetime(TRTSDTM[1]), lubridate::as_datetime(TRTENDT[1]), by = \"day\"), size = nlevels(AVISIT) )), each = n() / nlevels(AVISIT) )) %>% dplyr::ungroup() %>% dplyr::select(-TRTENDT) %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ADTM) tmc_ex_adqs <- adqs %>% dplyr::group_by(.data$USUBJID) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$AVISITN, .data$ADTM ) i_lbls <- sapply( names(col_labels(tmc_ex_adqs)[is.na(col_labels(tmc_ex_adqs))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adqs[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adqs, file = \"data/tmc_ex_adqs.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"adrs","dir":"Articles","previous_headings":"","what":"ADRS","title":"Example Data Generation","text":"","code":"generate_adrs <- function(adsl = tmc_ex_adsl) { set.seed(1) param_codes <- stats::setNames(1:5, c(\"CR\", \"PR\", \"SD\", \"PD\", \"NE\")) lookup_ars <- expand.grid( ARM = c(\"A: Drug X\", \"B: Placebo\", \"C: Combination\"), AVALC = names(param_codes) ) %>% dplyr::mutate( AVAL = param_codes[.data$AVALC], p_scr = c(rep(0, 3), rep(0, 3), c(1, 1, 1), c(0, 0, 0), c(0, 0, 0)), p_bsl = c(rep(0, 3), rep(0, 3), c(1, 1, 1), c(0, 0, 0), c(0, 0, 0)), p_cycle = c(c(.35, .25, .4), c(.30, .20, .20), c(.2, .25, .3), c(.14, 0.20, 0.18), c(.01, 0.1, 0.02)), p_eoi = c(c(.35, .25, .4), c(.30, .20, .20), c(.2, .25, .3), c(.14, 0.20, 0.18), c(.01, 0.1, 0.02)), p_fu = c(c(.25, .15, .3), c(.15, .05, .25), c(.3, .25, .3), c(.3, .55, .25), rep(0, 3)) ) adrs <- split(adsl, adsl$USUBJID) %>% lapply(function(pinfo) { probs <- dplyr::filter(lookup_ars, .data$ARM == as.character(pinfo$ACTARM)) # screening rsp_screen <- sample(probs$AVALC, 1, prob = probs$p_scr) %>% as.character() # baseline rsp_bsl <- sample(probs$AVALC, 1, prob = probs$p_bsl) %>% as.character() # cycle rsp_c2d1 <- sample(probs$AVALC, 1, prob = probs$p_cycle) %>% as.character() rsp_c4d1 <- sample(probs$AVALC, 1, prob = probs$p_cycle) %>% as.character() # end of induction rsp_eoi <- sample(probs$AVALC, 1, prob = probs$p_eoi) %>% as.character() # follow up rsp_fu <- sample(probs$AVALC, 1, prob = probs$p_fu) %>% as.character() best_rsp <- min(param_codes[c(rsp_screen, rsp_bsl, rsp_eoi, rsp_fu, rsp_c2d1, rsp_c4d1)]) best_rsp_i <- which.min(param_codes[c(rsp_screen, rsp_bsl, rsp_eoi, rsp_fu, rsp_c2d1, rsp_c4d1)]) avisit <- c(\"SCREENING\", \"BASELINE\", \"CYCLE 2 DAY 1\", \"CYCLE 4 DAY 1\", \"END OF INDUCTION\", \"FOLLOW UP\") # meaningful date information TRTSTDT <- lubridate::date(pinfo$TRTSDTM) TRTENDT <- lubridate::date(dplyr::if_else( !is.na(pinfo$TRTEDTM), pinfo$TRTEDTM, lubridate::floor_date(TRTSTDT + study_duration_secs, unit = \"day\") )) scr_date <- TRTSTDT - lubridate::days(100) bs_date <- TRTSTDT flu_date <- sample(seq(lubridate::as_datetime(TRTSTDT), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1) eoi_date <- sample(seq(lubridate::as_datetime(TRTSTDT), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1) c2d1_date <- sample(seq(lubridate::as_datetime(TRTSTDT), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1) c4d1_date <- min(lubridate::date(c2d1_date + lubridate::days(60)), TRTENDT) tibble::tibble( STUDYID = pinfo$STUDYID, USUBJID = pinfo$USUBJID, PARAMCD = as.factor(c(rep(\"OVRINV\", 6), \"BESRSPI\", \"INVET\")), PARAM = as.factor(dplyr::recode( .data$PARAMCD, OVRINV = \"Overall Response by Investigator - by visit\", OVRSPI = \"Best Overall Response by Investigator (no confirmation required)\", BESRSPI = \"Best Confirmed Overall Response by Investigator\", INVET = \"Investigator End Of Induction Response\" )), AVALC = c( rsp_screen, rsp_bsl, rsp_c2d1, rsp_c4d1, rsp_eoi, rsp_fu, names(param_codes)[best_rsp], rsp_eoi ), AVAL = param_codes[.data$AVALC], AVISIT = factor(c(avisit, avisit[best_rsp_i], avisit[5]), levels = avisit) ) %>% merge( tibble::tibble( AVISIT = avisit, ADTM = c(scr_date, bs_date, c2d1_date, c4d1_date, eoi_date, flu_date), AVISITN = c(-1, 0, 2, 4, 999, 999), TRTSDTM = pinfo$TRTSDTM ) %>% dplyr::select(-\"TRTSDTM\"), by = \"AVISIT\" ) }) %>% Reduce(rbind, .) %>% dplyr::mutate( AVALC = factor(.data$AVALC, levels = names(param_codes)), DTHFL = factor(sample(c(\"Y\", \"N\"), nrow(.), replace = TRUE, prob = c(1, 0.8))) %>% with_label(\"Death Flag\") ) # merge ADSL to be able to add RS date and study day variables adrs <- dplyr::inner_join( adsl, adrs, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) tmc_ex_adrs <- adrs %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$AVISITN, .data$ADTM ) i_lbls <- sapply( names(col_labels(tmc_ex_adrs)[is.na(col_labels(tmc_ex_adrs))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adrs[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adrs, file = \"data/tmc_ex_adrs.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"adtte","dir":"Articles","previous_headings":"","what":"ADTTE","title":"Example Data Generation","text":"","code":"generate_adtte <- function(adsl = tmc_ex_adsl) { set.seed(1) lookup_tte <- tibble::tribble( ~ARM, ~PARAMCD, ~PARAM, ~LAMBDA, ~CNSR_P, \"ARM A\", \"OS\", \"Overall Survival\", log(2) / 610, 0.4, \"ARM B\", \"OS\", \"Overall Survival\", log(2) / 490, 0.3, \"ARM C\", \"OS\", \"Overall Survival\", log(2) / 365, 0.2, \"ARM A\", \"PFS\", \"Progression Free Survival\", log(2) / 365, 0.4, \"ARM B\", \"PFS\", \"Progression Free Survival\", log(2) / 305, 0.3, \"ARM C\", \"PFS\", \"Progression Free Survival\", log(2) / 243, 0.2, \"ARM A\", \"EFS\", \"Event Free Survival\", log(2) / 365, 0.4, \"ARM B\", \"EFS\", \"Event Free Survival\", log(2) / 305, 0.3, \"ARM C\", \"EFS\", \"Event Free Survival\", log(2) / 243, 0.2, \"ARM A\", \"CRSD\", \"Duration of Confirmed Response\", log(2) / 305, 0.4, \"ARM B\", \"CRSD\", \"Duration of Confirmed Response\", log(2) / 243, 0.3, \"ARM C\", \"CRSD\", \"Duration of Confirmed Response\", log(2) / 182, 0.2 ) evntdescr_sel <- c( \"Death\", \"Disease Progression\", \"Last Tumor Assessment\", \"Adverse Event\", \"Last Date Known To Be Alive\" ) cnsdtdscr_sel <- c( \"Preferred Term\", \"Clinical Cut Off\", \"Completion or Discontinuation\", \"End of AE Reporting Period\" ) adtte <- split(adsl, adsl$USUBJID) %>% lapply(FUN = function(pinfo) { lookup_tte %>% dplyr::filter(.data$ARM == as.character(pinfo$ACTARMCD)) %>% dplyr::rowwise() %>% dplyr::mutate( STUDYID = pinfo$STUDYID, USUBJID = pinfo$USUBJID, CNSR = sample(c(0, 1), 1, prob = c(1 - .data$CNSR_P, .data$CNSR_P)), AVAL = stats::rexp(1, .data$LAMBDA), AVALU = \"DAYS\", EVNTDESC = if (.data$CNSR == 1) { sample(evntdescr_sel[-c(1:2)], 1) } else { ifelse(.data$PARAMCD == \"OS\", sample(evntdescr_sel[1], 1), sample(evntdescr_sel[c(1:2)], 1) ) } ) %>% dplyr::select(-\"LAMBDA\", -\"CNSR_P\") }) %>% Reduce(rbind, .) # merge ADSL to be able to add TTE date and study day variables adtte <- dplyr::inner_join( adsl, dplyr::select(adtte, -\"ARM\"), by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::mutate(ADTM = sample( seq(lubridate::as_datetime(TRTSDTM), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1 )) %>% dplyr::select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ADTM) adtte <- adtte %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(PARAM = as.factor(.data$PARAM)) %>% dplyr::mutate(PARAMCD = as.factor(.data$PARAMCD)) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$ADTM ) lbls <- col_labels(adtte) # adding adverse event counts and log follow-up time tmc_ex_adtte <- dplyr::bind_rows( adtte, data.frame(adtte %>% dplyr::group_by(.data$USUBJID) %>% dplyr::slice_head(n = 1) %>% dplyr::mutate( PARAMCD = \"TNE\", PARAM = \"Total Number of Exacerbations\", AVAL = stats::rpois(1, 3), AVALU = \"COUNT\", lgTMATRSK = log(stats::rexp(1, rate = 3)), dplyr::across(c(\"ADTM\", \"EVNTDESC\"), ~NA) )) ) %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$ADTM ) col_labels(tmc_ex_adtte) <- c(lbls, lgTMATRSK = \"Log Time At Risk\") i_lbls <- sapply( names(col_labels(tmc_ex_adtte)[is.na(col_labels(tmc_ex_adtte))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adtte[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adtte, file = \"data/tmc_ex_adtte.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"advs","dir":"Articles","previous_headings":"","what":"ADVS","title":"Example Data Generation","text":"","code":"generate_advs <- function(adsl = tmc_ex_adsl, n_assessments = 5L, n_days = 5L) { set.seed(1) param <- c( \"Diastolic Blood Pressure\", \"Pulse Rate\", \"Respiratory Rate\", \"Systolic Blood Pressure\", \"Temperature\", \"Weight\" ) paramcd <- c(\"DIABP\", \"PULSE\", \"RESP\", \"SYSBP\", \"TEMP\", \"WEIGHT\") paramu <- c(\"Pa\", \"beats/min\", \"breaths/min\", \"Pa\", \"C\", \"Kg\") visit_format <- \"WEEK\" param_init_list <- relvar_init(param, paramcd) unit_init_list <- relvar_init(param, paramu) advs <- expand.grid( STUDYID = unique(adsl$STUDYID), USUBJID = adsl$USUBJID, PARAM = as.factor(param_init_list$relvar1), AVISIT = visit_schedule(visit_format = visit_format, n_assessments = n_assessments), stringsAsFactors = FALSE ) advs <- dplyr::mutate( advs, AVISITN = dplyr::case_when( AVISIT == \"SCREENING\" ~ -1, AVISIT == \"BASELINE\" ~ 0, (grepl(\"^WEEK\", AVISIT) | grepl(\"^CYCLE\", AVISIT)) ~ as.numeric(AVISIT) - 2, TRUE ~ NA_real_ ) ) advs$PARAMCD <- as.factor(rel_var( df = advs, var_name = \"PARAMCD\", var_values = param_init_list$relvar2, related_var = \"PARAM\" )) advs$AVALU <- as.factor(rel_var( df = advs, var_name = \"AVALU\", var_values = unit_init_list$relvar2, related_var = \"PARAM\" )) advs$AVAL <- stats::rnorm(nrow(advs), mean = 50, sd = 8) advs <- advs[order(advs$STUDYID, advs$USUBJID, advs$PARAMCD, advs$AVISITN), ] advs <- dplyr::inner_join( adsl, advs, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::mutate(ADTM = sample( seq(lubridate::as_datetime(TRTSDTM), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1 )) %>% dplyr::mutate(ADY = ceiling(difftime(ADTM, TRTSDTM, units = \"days\"))) %>% dplyr::select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ADTM) tmc_ex_advs <- advs %>% dplyr::group_by(.data$USUBJID) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$AVISITN, .data$ADTM ) i_lbls <- sapply( names(col_labels(tmc_ex_advs)[is.na(col_labels(tmc_ex_advs))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_advs[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_advs, file = \"data/tmc_ex_advs.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/generate_tmc_test_data.html","id":"generate-data","dir":"Articles","previous_headings":"","what":"Generate Data","title":"Example Data Generation","text":"","code":"# Generate & load adsl tmp_fol <- getwd() setwd(dirname(tmp_fol)) generate_adsl() load(\"data/tmc_ex_adsl.rda\") # Generate other datasets generate_adae() generate_adaette() generate_adcm() generate_adeg() generate_adex() generate_adlb() generate_admh() generate_adqs() generate_adrs() generate_adtte() generate_advs() setwd(tmp_fol)"},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/quickstart_substitute.html","id":"section","dir":"Articles","previous_headings":"","what":"Quick start: `substitute` for NSE","title":"Quick start: `substitute` for NSE","text":"Considering expression, R usually evaluates returns value. Instead focusing value, also possible work code generated value. non standard evaluation, NSE, starts. function substitute important element non-standard evaluation. instance, consider defined <- 5, expression returns 5, substitute() returns code obtain value: . principle teal relies : generate expressions. return result expression result panel app. return corresponding code (expression) Show R Code. expression returning displayed value must reactive. information encoding one hand, filtering panel hand modify expression displayed value. , teal needs work expressions values relies heavily NSE. NSE advanced notion mixing Shiny app development source difficulties : hindered coding efficiency Shiny app must run order check correct execution code. limited possibilities testing. alternative, possible focus first NSE aspects plain R, ready, integrate Shiny App. following practical examples demonstrating NSE works. choice made focus substitute.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/quickstart_substitute.html","id":"nse-principle","dir":"Articles","previous_headings":"The Basics","what":"NSE Principle","title":"Quick start: `substitute` for NSE","text":"happened? substitute returns code value, attempt run code, therefore possible return expression make sense (yet), instance involving two non defined objects. values b exist, expression can run without error: Now, function name substitute reason. returning expression, also operates substitutions terms within given expression. happened? objects b exist function environment substitute called. terms expression within substitute replaced values b. Indeed, returning expression, substitute verifies b don’t value existing evaluation environment. , values b used expression. also possible use second argument substitute, env, environment (list) containing objects. expression submitted substitute corresponding objects env, terms within expression substituted provided values: happened? environment values b taken directly declared within substitute expression (argument expr) values substituted (argument env). substitute returned non-evaluated expression, use eval() evaluate . slightly elaborate expression: Note : x argument name plot preserved, x object replaced.","code":"non_evaluated_expression <- substitute(expr = a + b) non_evaluated_expression ## a + b eval(non_evaluated_expression) ## Error in eval(non_evaluated_expression): object 'b' not found non_evaluated_expression <- substitute(expr = a + b) a <- 1 b <- 5 eval(non_evaluated_expression) ## [1] 6 fun <- function(a, b) { substitute(expr = a + b) } non_evaluated_expression <- fun(5, -2) non_evaluated_expression ## 5 + -2 eval(non_evaluated_expression) ## [1] 3 non_evaluated_expression <- substitute( expr = a + b, env = list(a = 5, b = 5) ) non_evaluated_expression ## 5 + 5 eval(non_evaluated_expression) ## [1] 10 non_evaluated_expression <- substitute( expr = plot(x = x, y = exp(x), main = text), env = list(x = 0:10, text = \"A graph\") ) non_evaluated_expression ## plot(x = 0:10, y = exp(0:10), main = \"A graph\") eval(non_evaluated_expression)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/quickstart_substitute.html","id":"replace-an-object-name","dir":"Articles","previous_headings":"The Basics","what":"Replace an object name","title":"Quick start: `substitute` for NSE","text":"formulas, character strings accepted, execute substitution? object names specific class (name); .names coerces character string object name (alternatively, .symbol provides identical result):","code":"# Error expected: plot_expr <- substitute( expr = plot(y ~ x, data = iris, main = text), env = list( x = Sepal.Length, y = Sepal.Width, text = \"Iris, again ...\" ) ) ## Error: object 'Sepal.Length' not found # Error expected: plot_expr <- substitute( expr = plot(y ~ x, data = iris, main = text), env = list( x = \"Sepal.Length\", y = \"Sepal.Width\", text = \"Iris, again ...\" ) ) plot_expr ## plot(\"Sepal.Width\" ~ \"Sepal.Length\", data = iris, main = \"Iris, again ...\") eval(plot_expr) ## Error in terms.formula(formula, data = data): invalid term in model formula plot_expr <- substitute( expr = plot(y ~ x, data = iris, main = text), env = list( x = as.name(\"Sepal.Length\"), y = as.symbol(\"Sepal.Width\"), text = \"Iris, again ...\" ) ) plot_expr ## plot(Sepal.Width ~ Sepal.Length, data = iris, main = \"Iris, again ...\") eval(plot_expr)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/quickstart_substitute.html","id":"what-about-dataframe-names","dir":"Articles","previous_headings":"The Basics","what":"What about dataframe names?","title":"Quick start: `substitute` for NSE","text":"Lets imagine pipe-flavored expression, df term corresponding dataframe substituted: df %>% plot(y ~ x, data = ., main = text). principle exposed can work directly without addition. However, df expression replaced directly value object provided expression generating dataframe: pipeline working humanly readable. can replace value expression generating value? pretty much topic vignette: substitute.","code":"library(dplyr) ## Error in get(paste0(generic, \".\", class), envir = get_method_env()) : ## object 'type_sum.accel' not found ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union short_iris <- head(iris) plot_expr <- substitute( expr = df %>% plot(y ~ x, data = ., main = text), env = list( df = short_iris, x = as.name(\"Sepal.Length\"), y = as.symbol(\"Sepal.Width\"), text = \"Iris, again ...\" ) ) eval(plot_expr) plot_expr ## list(Sepal.Length = c(5.1, 4.9, 4.7, 4.6, 5, 5.4), Sepal.Width = c(3.5, ## 3, 3.2, 3.1, 3.6, 3.9), Petal.Length = c(1.4, 1.4, 1.3, 1.5, ## 1.4, 1.7), Petal.Width = c(0.2, 0.2, 0.2, 0.2, 0.2, 0.4), Species = c(1L, ## 1L, 1L, 1L, 1L, 1L)) %>% plot(Sepal.Width ~ Sepal.Length, data = ., ## main = \"Iris, again ...\") plot_expr <- substitute( expr = df %>% plot(y ~ x, data = ., main = text), env = list( df = substitute(iris), x = as.name(\"Sepal.Length\"), y = as.symbol(\"Sepal.Width\"), text = \"Iris, again ...\" ) ) plot_expr ## iris %>% plot(Sepal.Width ~ Sepal.Length, data = ., main = \"Iris, again ...\") eval(plot_expr)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/quickstart_substitute.html","id":"in-a-nutshell","dir":"Articles","previous_headings":"The Basics","what":"In a nutshell","title":"Quick start: `substitute` for NSE","text":"expr expression (eventually) substituted. env environment potential replacement value might needed. object name (like formulas e.g. y ~ x) , use .name .symbol. data frame name (like iris) , use substitute.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/quickstart_substitute.html","id":"direct-use-of-substitute","dir":"Articles","previous_headings":"rtables","what":"Direct use of substitute","title":"Quick start: `substitute` for NSE","text":"substitute approach can used rtables pipelines. Lets prepare example reporting data LB domain. example based template LBT01; target report columns lab test result per study arm, values (AVAL) changes baseline (CHG), per analysis visit rows. data can prepared follows: rtables expression obtained : expression valid … : … easily readable …: … can arranged:","code":"library(teal.modules.clinical) library(dplyr) adlb <- tmc_ex_adlb adlb_f <- adlb %>% filter( PARAM == \"Alanine Aminotransferase Measurement\" & ARMCD %in% c(\"ARM A\", \"ARM B\") & AVISIT == \"WEEK 1 DAY 8\" ) rtables_expr <- substitute( expr = basic_table() %>% split_cols_by(arm, split_fun = drop_split_levels) %>% split_rows_by(visit, split_fun = drop_split_levels) %>% split_cols_by_multivar( vars = c(\"AVAL\", \"CHG\"), varlabels = c(\"Value\", \"Change\") ) %>% summarize_colvars() %>% build_table(df = df), env = list( df = substitute(adlb_f), arm = \"ARM\", visit = \"AVISIT\" ) ) eval(rtables_expr) ## A: Drug X B: Placebo ## Value Change Value Change ## —————————————————————————————————————————————————————————————————————— ## WEEK 1 DAY 8 ## n 69 69 73 73 ## Mean (SD) 20.8 (4.1) 1.6 (6.1) 20.2 (4.1) -0.2 (5.6) ## Median 20.4 2.4 20.0 -0.2 ## Min - Max 12.8 - 34.6 -11.3 - 14.2 12.6 - 29.0 -12.8 - 10.8 rtables_expr ## basic_table() %>% split_cols_by(\"ARM\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISIT\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c(\"Value\", ## \"Change\")) %>% summarize_colvars() %>% build_table(df = adlb_f) library(teal) library(styler) #' Stylish code #' #' Deparse an expression and display the code following NEST conventions. #' #' @param expr (`call`)\\cr or possibly understood as so. #' styled_expr <- function(expr) { print( styler::style_text(text = deparse(expr)), colored = FALSE ) } #' #' @examples styled_expr(rtables_expr) ## basic_table() %>% ## split_cols_by(\"ARM\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISIT\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c( ## \"Value\", ## \"Change\" ## )) %>% ## summarize_colvars() %>% ## build_table(df = adlb_f)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/quickstart_substitute.html","id":"substitute-in-a-function","dir":"Articles","previous_headings":"rtables","what":"substitute in a function","title":"Quick start: `substitute` for NSE","text":"Moving , substitute can actually wrapped function, way rtables pipelines programmatically obtained: results obtained … , fine tuning easier. instance, variable designating study arm visit can changed, expected feature teal module encoding panel.","code":"rtables_expr <- function(df, arm, visit) { substitute( expr = basic_table() %>% split_cols_by(arm, split_fun = drop_split_levels) %>% split_rows_by(visit, split_fun = drop_split_levels) %>% split_cols_by_multivar( vars = c(\"AVAL\", \"CHG\"), varlabels = c(\"Value\", \"Change\") ) %>% summarize_colvars() %>% build_table(df = df), env = list( df = substitute(df), arm = arm, visit = visit ) ) } result <- rtables_expr(df = adlb_f, arm = \"ARM\", visit = \"AVISIT\") styled_expr(result) ## basic_table() %>% ## split_cols_by(\"ARM\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISIT\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c( ## \"Value\", ## \"Change\" ## )) %>% ## summarize_colvars() %>% ## build_table(df = adlb_f) eval(result) ## A: Drug X B: Placebo ## Value Change Value Change ## —————————————————————————————————————————————————————————————————————— ## WEEK 1 DAY 8 ## n 69 69 73 73 ## Mean (SD) 20.8 (4.1) 1.6 (6.1) 20.2 (4.1) -0.2 (5.6) ## Median 20.4 2.4 20.0 -0.2 ## Min - Max 12.8 - 34.6 -11.3 - 14.2 12.6 - 29.0 -12.8 - 10.8 result <- rtables_expr(df = adlb_f, arm = \"ARMCD\", visit = \"AVISITN\") eval(result) ## Split var [AVISITN] was not character or factor. Converting to factor ## ARM A ARM B ## Value Change Value Change ## ————————————————————————————————————————————————————————————————————— ## 1 ## n 69 69 73 73 ## Mean (SD) 20.8 (4.1) 1.6 (6.1) 20.2 (4.1) -0.2 (5.6) ## Median 20.4 2.4 20.0 -0.2 ## Min - Max 12.8 - 34.6 -11.3 - 14.2 12.6 - 29.0 -12.8 - 10.8 styled_expr(result) ## basic_table() %>% ## split_cols_by(\"ARMCD\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISITN\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c( ## \"Value\", ## \"Change\" ## )) %>% ## summarize_colvars() %>% ## build_table(df = adlb_f)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/quickstart_substitute.html","id":"chain-expressions-in-a-pipeline","dir":"Articles","previous_headings":"rtables","what":"Chain expressions in a pipeline","title":"Quick start: `substitute` for NSE","text":"also possible manipulate expressions, instance, expressions might chained pipeline. Expressions can arranged list, way, possible conditional editing expressions. context rtables, layers enclosing analyze call handle .stats option. lean expression include .stats option, default value changed. expected feature teal module rendering code Show R Code: First application standard statistics: statistics specifications:","code":"#' Expressions as a pipeline #' #' Accepts expressions to be chained using the `magrittr` pipeline-flavor. #' @param ... (`call`)\\cr or object which can be interpreted as so. #' (e.g. `name`) #' pipe_expr <- function(...) { exprs <- unlist(list(...)) exprs <- lapply( exprs, function(x) { x <- deparse(x) paste(x, collapse = \" \") } ) exprs <- unlist(exprs) exprs <- paste(exprs, collapse = \" %>% \") str2lang(exprs) } #' @examples result <- pipe_expr( expr1 = substitute(df), expr2 = substitute(head) ) result ## df %>% head rtables_expr <- function(df, arm, visit, .stats = NULL) { # The rtables layout is decomposed into a list of expressions. lyt <- list() # 1. First the columns and rows: lyt$structure <- substitute( expr = basic_table() %>% split_cols_by(arm, split_fun = drop_split_levels) %>% split_rows_by(visit, split_fun = drop_split_levels) %>% split_cols_by_multivar( vars = c(\"AVAL\", \"CHG\"), varlabels = c(\"Value\", \"Change\") ), env = list( arm = arm, visit = visit ) ) # 2. The analyze layer which depends on the use of .stats. lyt$analyze <- if (is.null(.stats)) { substitute( summarize_colvars() ) } else { substitute( summarize_colvars(.stats = .stats), list(.stats = .stats) ) } # 3. And finishing with rtables::build_table. lyt$build <- substitute( build_table(df = df), list(df = substitute(df)) ) # As previously demonstrated, expressions can be manipulated and # chained in a pipeline. pipe_expr(lyt) } result <- rtables_expr(df = adlb_f, arm = \"ARM\", visit = \"AVISIT\") styled_expr(result) ## basic_table() %>% ## split_cols_by(\"ARM\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISIT\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c( ## \"Value\", ## \"Change\" ## )) %>% ## summarize_colvars() %>% ## build_table(df = adlb_f) eval(result) ## A: Drug X B: Placebo ## Value Change Value Change ## —————————————————————————————————————————————————————————————————————— ## WEEK 1 DAY 8 ## n 69 69 73 73 ## Mean (SD) 20.8 (4.1) 1.6 (6.1) 20.2 (4.1) -0.2 (5.6) ## Median 20.4 2.4 20.0 -0.2 ## Min - Max 12.8 - 34.6 -11.3 - 14.2 12.6 - 29.0 -12.8 - 10.8 result <- rtables_expr( df = adlb_f, arm = \"ARM\", visit = \"AVISIT\", .stats = c(\"n\", \"mean_sd\") ) styled_expr(result) ## basic_table() %>% ## split_cols_by(\"ARM\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISIT\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c( ## \"Value\", ## \"Change\" ## )) %>% ## summarize_colvars(.stats = c(\"n\", \"mean_sd\")) %>% ## build_table(df = adlb_f) eval(result) ## A: Drug X B: Placebo ## Value Change Value Change ## ——————————————————————————————————————————————————————————————— ## WEEK 1 DAY 8 ## n 69 69 73 73 ## Mean (SD) 20.8 (4.1) 1.6 (6.1) 20.2 (4.1) -0.2 (5.6)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/quickstart_substitute.html","id":"including-pre-processing","dir":"Articles","previous_headings":"rtables","what":"Including pre-processing","title":"Quick start: `substitute` for NSE","text":"Finally, also possible wrap several expressions single function. instance, teal module generally includes pre-processing section: now possible modify studied parameter (PARAMCD) addition study arm visit variables names. two expressions consistent: two expressions can executed return rtables:","code":"rtables_expr <- function(df, paramcd, arm, visit, .stats = NULL) { # y is a list which will collect two expressions: # 1. y$data with the preprocessing steps. # 2. y$rtables the table layout and build. y <- list() # 1. Preprocessing --- y$data <- substitute( df <- df %>% filter( PARAMCD == paramcd & ARMCD %in% c(\"ARM A\", \"ARM B\") & AVISIT == \"WEEK 1 DAY 8\" ), list( df = substitute(df), paramcd = paramcd ) ) # 2. rtables layout --- lyt <- list() lyt$structure <- substitute( expr = basic_table() %>% split_cols_by(arm, split_fun = drop_split_levels) %>% split_rows_by(visit, split_fun = drop_split_levels) %>% split_cols_by_multivar( vars = c(\"AVAL\", \"CHG\"), varlabels = c(\"Value\", \"Change\") ), env = list( arm = arm, visit = visit ) ) lyt$analyze <- if (is.null(.stats)) { substitute( summarize_colvars() ) } else { substitute( summarize_colvars(.stats = .stats), list(.stats = .stats) ) } lyt$build <- substitute( build_table(df = df), list(df = substitute(df)) ) y$rtables <- pipe_expr(lyt) # Finally returns y as a list with two expressions. y } adlb <- tmc_ex_adlb result <- rtables_expr( df = adlb, paramcd = \"CRP\", arm = \"ARM\", visit = \"AVISIT\", .stats = c(\"n\", \"mean_sd\") ) styled_expr(result$data) ## adlb <- adlb %>% filter(PARAMCD == \"CRP\" & ARMCD %in% c( ## \"ARM A\", ## \"ARM B\" ## ) & AVISIT == \"WEEK 1 DAY 8\") styled_expr(result$rtables) ## basic_table() %>% ## split_cols_by(\"ARM\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISIT\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c( ## \"Value\", ## \"Change\" ## )) %>% ## summarize_colvars(.stats = c(\"n\", \"mean_sd\")) %>% ## build_table(df = adlb) result_exec <- mapply(eval, result) result_exec$rtables ## A: Drug X B: Placebo ## Value Change Value Change ## ———————————————————————————————————————————————————————————— ## WEEK 1 DAY 8 ## n 69 69 73 73 ## Mean (SD) 1.0 (0.2) 0.0 (0.3) 1.0 (0.2) 0.0 (0.3)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/quickstart_substitute.html","id":"in-a-nutshell-1","dir":"Articles","previous_headings":"rtables","what":"In a nutshell","title":"Quick start: `substitute` for NSE","text":"point, possible : generate rtables pipelines. chain expressions pipeline (e.g. pipe_expr) decompose rtables pipeline add conditional layers (e.g. .stats). group expressions single list control pre-processing rtables pipeline.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/teal-modules-clinical.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Getting Started with {teal.modules.clinical}","text":"teal.modules.clinical package implementing number teal modules helpful exploring clinical trials data, specifically targeted towards data following ADaM standards. teal.modules.clinical modules can used data ADaM standard clinical data, features package tailored towards data type. concepts presented require knowledge core features teal, specifically launch teal application pass data . Therefore, highly recommended refer home page introductory vignette teal package.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/teal-modules-clinical.html","id":"main-features","dir":"Articles","previous_headings":"","what":"Main Features","title":"Getting Started with {teal.modules.clinical}","text":"package provides ready--use teal modules can embed teal application. modules generate highly customizable tables, plots, outputs often used exploratory data analysis, including: ANCOVA - tm_t_ancova() Cox regression - tm_t_coxreg() Kaplan-Meier plot - tm_g_km() Logistic regression - tm_t_logistic() Bar chart - tm_g_barchart_simple() Confidence interval plot - tm_g_ci() Binary outcome response table - tm_t_binary_outcome() Summary adverse events table - tm_t_events_summary() SMQ table - tm_t_smq() Time--event table - tm_t_tte() library also offers group patient profile modules targeted clinical statisticians physicians want review data per patient basis. modules present data patient’s adverse events, severity, current therapy, laboratory results . See full index package functions & modules .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/teal-modules-clinical.html","id":"a-simple-application","dir":"Articles","previous_headings":"","what":"A Simple Application","title":"Getting Started with {teal.modules.clinical}","text":"teal.modules.clinical module needs embedded inside shiny/teal application interact . simple application including bar chart module look like :","code":"library(teal.modules.clinical) library(nestcolor) ADSL <- tmc_ex_adsl ADAE <- tmc_ex_adae app <- init( data = cdisc_data( ADSL = ADSL, ADAE = ADAE, code = \" ADSL <- tmc_ex_adsl ADAE <- tmc_ex_adae \" ), modules = list( tm_g_barchart_simple( label = \"ADAE Analysis\", x = data_extract_spec( dataname = \"ADAE\", select = select_spec( choices = variable_choices( ADAE, c( \"ARM\", \"ACTARM\", \"SEX\", \"RACE\", \"SAFFL\", \"STRATA2\" ) ), selected = \"ACTARM\", multiple = FALSE ) ) ) ) ) shinyApp(app$ui, app$server)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/articles/teal-modules-clinical.html","id":"try-it-out-in-shinylive","dir":"Articles","previous_headings":"A Simple Application","what":"Try it out in Shinylive","title":"Getting Started with {teal.modules.clinical}","text":"Open Shinylive Consider consulting documentation examples module (e.g. ?tm_g_barchart_simple). many, can also find useful links TLG Catalog additional example apps can found. teal.modules.clinical exports modules needs support libraries run teal app flesh functionality. example , tm_g_barchart_simple() function teal.modules.clinical whereas init() teal function, data_extract_spec(), select_spec(), variable_choices() teal.transform functions, cdisc_data() teal.data function. Let’s break app pieces: lines load libraries used example. use example data provided teal.modules.clinical package: nestcolor optional package can loaded apply standardized NEST color palette module plots. need load teal teal.modules.clinical already depends . next step, use teal create shiny UI server functions can launch using shiny. data argument tells teal input data - ADaM datasets ADSL ADAE - modules argument indicates modules included application. , include one module: tm_g_barchart_simple(). Finally, use shiny launch application: teal.modules.clinical modules allow specification arguments using teal.transform::choices_selected(), tm_t_summary() module following example. Please refer API reference specific modules examples information customization options available.","code":"library(teal.modules.clinical) library(nestcolor) ADSL <- tmc_ex_adsl ADAE <- tmc_ex_adae app <- init( data = cdisc_data( ADSL = ADSL, ADAE = ADAE, code = \" ADSL <- tmc_ex_adsl ADAE <- tmc_ex_adae \" ), modules = list( tm_g_barchart_simple( label = \"ADAE Analysis\", x = data_extract_spec( dataname = \"ADAE\", select = select_spec( choices = variable_choices( ADAE, c( \"ARM\", \"ACTARM\", \"SEX\", \"RACE\", \"SAFFL\", \"STRATA2\" ) ), selected = \"ACTARM\", multiple = FALSE ) ) ) ) ) if (interactive()) shinyApp(app$ui, app$server) ADSL <- tmc_ex_adsl app <- init( data = cdisc_data(ADSL = ADSL, code = \"ADSL <- tmc_ex_adsl\"), modules = list( tm_t_summary( label = \"Demographic Table\", dataname = \"ADSL\", arm_var = choices_selected(choices = c(\"ARM\", \"ARMCD\"), selected = \"ARM\"), summarize_vars = choices_selected( choices = c(\"SEX\", \"RACE\", \"BMRKR2\", \"EOSDY\", \"DCSREAS\", \"AGE\"), selected = c(\"SEX\", \"RACE\") ) ) ) ) if (interactive()) shinyApp(app$ui, app$server)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Joe Zhu. Author, maintainer. Jana Stoilova. Author. Davide Garolini. Author. Emily de la Rua. Author. Abinaya Yogasekaram. Author. Mahmoud Hallal. Author. Dawid Kaledkowski. Author. Rosemary Li. Author. Heng Wang. Author. Pawel Rucki. Author. Nikolas Burkoff. Author. Konrad Pagacz. Author. Vaakesan Sundrelingam. Contributor. Francois Collin. Contributor. Imanol Zubizarreta. Contributor. F. Hoffmann-La Roche AG. Copyright holder, funder.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Zhu J, Stoilova J, Garolini D, de la Rua E, Yogasekaram , Hallal M, Kaledkowski D, Li R, Wang H, Rucki P, Burkoff N, Pagacz K (2024). teal.modules.clinical: 'teal' Modules Standard Clinical Outputs. R package version 0.9.1.9042, https://github.com/insightsengineering/teal.modules.clinical/, https://insightsengineering.github.io/teal.modules.clinical/.","code":"@Manual{, title = {teal.modules.clinical: 'teal' Modules for Standard Clinical Outputs}, author = {Joe Zhu and Jana Stoilova and Davide Garolini and Emily {de la Rua} and Abinaya Yogasekaram and Mahmoud Hallal and Dawid Kaledkowski and Rosemary Li and Heng Wang and Pawel Rucki and Nikolas Burkoff and Konrad Pagacz}, year = {2024}, note = {R package version 0.9.1.9042, https://github.com/insightsengineering/teal.modules.clinical/}, url = {https://insightsengineering.github.io/teal.modules.clinical/}, }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/index.html","id":"tealmodulesclinical","dir":"","previous_headings":"","what":"teal Modules for Standard Clinical Outputs","title":"teal Modules for Standard Clinical Outputs","text":"package contains set standard teal modules used CDISC data order generate many standard outputs used clinical trials. modules include, limited : Forest plots (tm_g_forest_rsp()/tm_g_forest_tte()) Line plots (tm_g_lineplot()) Kaplan-Meier plots (tm_g_km()) … MMRM (tm_a_mmrm()) Logistic regression (tm_t_logistic()) Cox regression (tm_t_coxreg()) … Unique patients (tm_t_summary()) Exposure across patients (tm_t_exposure()) Change baseline parameters (tm_t_summary_by()) … Table basic information chosen patient (tm_t_pp_basic_info()) Plot patient vitals time (tm_g_pp_vitals()) General timeline individual patients (tm_g_pp_patient_timeline()) … modules package implemented using functions R package tern order produce output. Please see Teal Gallery TLG Catalog examples shiny apps created using modules package.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"teal Modules for Standard Clinical Outputs","text":"Alternatively, might want use development version.","code":"install.packages('teal.modules.clinical') # install.packages(\"pak\") pak::pak(\"insightsengineering/teal.modules.clinical\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"teal Modules for Standard Clinical Outputs","text":"understand use package, please refer Getting Started article, provides multiple examples code implementation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/index.html","id":"playground","dir":"","previous_headings":"","what":"Playground","title":"teal Modules for Standard Clinical Outputs","text":"can try package without installing Shinylive: stable development","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/index.html","id":"getting-help","dir":"","previous_headings":"","what":"Getting help","title":"teal Modules for Standard Clinical Outputs","text":"encounter bug feature request, please file issue. questions, discussions, staying date, please use teal channel pharmaverse slack workspace.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/index.html","id":"acknowledgment","dir":"","previous_headings":"","what":"Acknowledgment","title":"teal Modules for Standard Clinical Outputs","text":"package result joint efforts many developers stakeholders. like thank everyone contributed far!","code":""},{"path":[]},{"path":[]},{"path":[]},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/add_expr.html","id":null,"dir":"Reference","previous_headings":"","what":"Expression List — add_expr","title":"Expression List — add_expr","text":"Add new expression list (expressions).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/add_expr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Expression List — add_expr","text":"","code":"add_expr(expr_ls, new_expr)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/add_expr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Expression List — add_expr","text":"expr_ls (list call) list new expression added. new_expr (call) new expression add.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/add_expr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Expression List — add_expr","text":"list call.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/add_expr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Expression List — add_expr","text":"Offers stricter control add new expressions existing list. list expressions can later used generate pipeline, instance pipe_expr.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/add_expr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Expression List — add_expr","text":"","code":"library(rtables) lyt <- list() lyt <- add_expr(lyt, substitute(basic_table())) lyt <- add_expr( lyt, substitute(split_cols_by(var = arm), env = list(armcd = \"ARMCD\")) ) lyt <- add_expr( lyt, substitute( test_proportion_diff( vars = \"rsp\", method = \"cmh\", variables = list(strata = \"strata\") ) ) ) lyt <- add_expr(lyt, quote(build_table(df = dta))) pipe_expr(lyt) #> basic_table() %>% split_cols_by(var = arm) %>% test_proportion_diff(vars = \"rsp\", #> method = \"cmh\", variables = list(strata = \"strata\")) %>% #> build_table(df = dta)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/arm_ref_comp_observer.html","id":null,"dir":"Reference","previous_headings":"","what":"Observer for Treatment reference variable — arm_ref_comp_observer","title":"Observer for Treatment reference variable — arm_ref_comp_observer","text":"Updates reference comparison Treatments selected Treatment variable changes","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/arm_ref_comp_observer.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Observer for Treatment reference variable — arm_ref_comp_observer","text":"","code":"arm_ref_comp_observer( session, input, output, id_ref = \"Ref\", id_comp = \"Comp\", id_arm_var, data, arm_ref_comp, module, on_off = reactive(TRUE), input_id = \"buckets\", output_id = \"arms_buckets\" )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/arm_ref_comp_observer.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Observer for Treatment reference variable — arm_ref_comp_observer","text":"session (environment) shiny session input (character) shiny input output (character) shiny input id_ref (character) id reference Treatment input UI element id_comp (character) id comparison group input UI element id_arm_var (character) id Treatment variable input UI element data (reactive data.frame) dataset used validate Treatment reference inputs set id_ref input. arm_ref_comp (unknown) Treatment reference compare variables provided nested list Treatment variable corresponds list specifying default levels reference comparison treatments. module (character) name module called (used produce informative error messages) on_off (logical) reactive can used stop whole observer FALSE. input_id (character) unique id buckets referenced . output_id (character) name UI id output written .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/arm_ref_comp_observer.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Observer for Treatment reference variable — arm_ref_comp_observer","text":"Returns shinyvalidate::InputValidator checks least one reference comparison arm","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/as_num.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse text input to numeric vector — as_num","title":"Parse text input to numeric vector — as_num","text":"Generic parse text numeric vectors. initially designed robust interpretation text input teal modules.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/as_num.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse text input to numeric vector — as_num","text":"","code":"as_num(str) # Default S3 method as_num(str) # S3 method for class 'character' as_num(str) # S3 method for class 'numeric' as_num(str) # S3 method for class 'factor' as_num(str) # S3 method for class 'logical' as_num(str)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/as_num.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse text input to numeric vector — as_num","text":"str (vector) extract numeric .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/as_num.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Parse text input to numeric vector — as_num","text":"vector numeric directly parsed numeric boolean. list numeric parsed character string, character string associated list item.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/as_num.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Parse text input to numeric vector — as_num","text":"function intended extract numeric character string, factor levels, boolean return vector numeric.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/as_num.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse text input to numeric vector — as_num","text":"","code":"dta <- list( character = c(\"text10,20.5letter30.!\", \"!-.40$$-50e5[\", NA), factor = factor(c(\"]+60e-6, 7.7%%8L\", \"%90sep.100\\\"1L\", NA_character_)), numeric = c(1, -5e+2, NA), logical = c(TRUE, FALSE, NA) ) lapply(dta, as_num) #> $character #> $character[[1]] #> [1] 10.0 20.5 30.0 #> #> $character[[2]] #> [1] -4e-01 -5e+06 #> #> $character[[3]] #> [1] NA #> #> #> $factor #> $factor[[1]] #> [1] 0.00006 7.70000 8.00000 #> #> $factor[[2]] #> [1] 90.0 0.1 1.0 #> #> $factor[[3]] #> [1] NA #> #> #> $numeric #> [1] 1 -500 NA #> #> $logical #> [1] 1 0 NA #>"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/bracket_expr.html","id":null,"dir":"Reference","previous_headings":"","what":"Expressions in Brackets — bracket_expr","title":"Expressions in Brackets — bracket_expr","text":"Groups several expressions single bracketed expression.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/bracket_expr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Expressions in Brackets — bracket_expr","text":"","code":"bracket_expr(exprs)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/bracket_expr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Expressions in Brackets — bracket_expr","text":"exprs (list call) expressions concatenate single bracketed expression.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/bracket_expr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Expressions in Brackets — bracket_expr","text":"{ object. See base::Paren() details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/bracket_expr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Expressions in Brackets — bracket_expr","text":"","code":"adsl <- tmc_ex_adsl adrs <- tmc_ex_adrs expr1 <- substitute( expr = anl <- subset(df, PARAMCD == param), env = list(df = as.name(\"adrs\"), param = \"INVET\") ) expr2 <- substitute(expr = anl$rsp_lab <- d_onco_rsp_label(anl$AVALC)) expr3 <- substitute( expr = { anl$is_rsp <- anl$rsp_lab %in% c(\"Complete Response (CR)\", \"Partial Response (PR)\") } ) res <- bracket_expr(list(expr1, expr2, expr3)) eval(res) table(anl$rsp_lab, anl$is_rsp) #> #> FALSE TRUE #> Complete Response (CR) 0 60 #> Partial Response (PR) 0 45 #> Stable Disease (SD) 50 0 #> Progressive Disease (PD) 39 0 #> Not Evaluable (NE) 6 0"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/call_concatenate.html","id":null,"dir":"Reference","previous_headings":"","what":"Concatenate expressions via a binary operator — call_concatenate","title":"Concatenate expressions via a binary operator — call_concatenate","text":"e.g. combine + ggplot without introducing parentheses due associativity","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/call_concatenate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Concatenate expressions via a binary operator — call_concatenate","text":"","code":"call_concatenate(args, bin_op = \"+\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/call_concatenate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Concatenate expressions via a binary operator — call_concatenate","text":"args arguments concatenate operator bin_op binary operator concatenate ","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/call_concatenate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Concatenate expressions via a binary operator — call_concatenate","text":"call","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/call_concatenate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Concatenate expressions via a binary operator — call_concatenate","text":"","code":"library(ggplot2) # What we want to achieve call(\"+\", quote(f), quote(g)) #> f + g call(\"+\", quote(f), call(\"+\", quote(g), quote(h))) # parentheses not wanted #> f + (g + h) call(\"+\", call(\"+\", quote(f), quote(g)), quote(h)) # as expected without unnecessary parentheses #> f + g + h Reduce(function(existing, new) call(\"+\", existing, new), list(quote(f), quote(g), quote(h))) #> f + g + h # how we do it call_concatenate(list(quote(f), quote(g), quote(h))) #> f + g + h call_concatenate(list(quote(f))) #> f call_concatenate(list()) #> NULL call_concatenate( list(quote(ggplot(mtcars)), quote(geom_point(aes(wt, mpg)))) ) #> ggplot(mtcars) + geom_point(aes(wt, mpg)) eval( call_concatenate( list(quote(ggplot(mtcars)), quote(geom_point(aes(wt, mpg)))) ) )"},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/check_arm_ref_comp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if the Treatment variable is reference or compare — check_arm_ref_comp","text":"","code":"check_arm_ref_comp(x, df_to_check, module)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/check_arm_ref_comp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if the Treatment variable is reference or compare — check_arm_ref_comp","text":"x (character) Name variable df_to_check (data.frame) table check module (character) teal module ref comp called ","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/check_arm_ref_comp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if the Treatment variable is reference or compare — check_arm_ref_comp","text":"TRUE FALSE whether variable ref comp","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/clean_description.html","id":null,"dir":"Reference","previous_headings":"","what":"Clean up categorical variable description — clean_description","title":"Clean up categorical variable description — clean_description","text":"Cleaning categorical variable descriptions presenting.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/clean_description.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Clean up categorical variable description — clean_description","text":"","code":"clean_description(x)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/clean_description.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Clean up categorical variable description — clean_description","text":"x (character) vector categories descriptions.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/clean_description.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Clean up categorical variable description — clean_description","text":"string","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/clean_description.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Clean up categorical variable description — clean_description","text":"","code":"clean_description(\"Level A (other text)\") #> [1] \"Level A\" clean_description(\"A long string that should be shortened\") #> [1] \"A long string tha...\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/color_lab_values.html","id":null,"dir":"Reference","previous_headings":"","what":"Mapping function for Laboratory Table — color_lab_values","title":"Mapping function for Laboratory Table — color_lab_values","text":"Map value level characters values proper html tags, colors icons.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/color_lab_values.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Mapping function for Laboratory Table — color_lab_values","text":"","code":"color_lab_values( x, classes = c(\"HIGH\", \"NORMAL\", \"LOW\"), colors = list(HIGH = \"red\", NORMAL = \"grey\", LOW = \"blue\"), default_color = \"black\", icons = list(HIGH = \"glyphicon glyphicon-arrow-up\", LOW = \"glyphicon glyphicon-arrow-down\") )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/color_lab_values.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Mapping function for Laboratory Table — color_lab_values","text":"x (character) vector elements format (value level). classes (character) classes vector. colors (list) color per class. default_color (character) default color. icons (list) certain icons per level.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/color_lab_values.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Mapping function for Laboratory Table — color_lab_values","text":"character vector element formatted HTML tag corresponding value x.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/color_lab_values.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Mapping function for Laboratory Table — color_lab_values","text":"","code":"color_lab_values(c(\"LOW\", \"LOW\", \"HIGH\", \"NORMAL\", \"HIGH\")) #> LOW #> \"LOW<\/i><\/span>\" #> LOW #> \"LOW<\/i><\/span>\" #> HIGH #> \"HIGH<\/i><\/span>\" #> NORMAL #> \"NORMAL<\/i><\/span>\" #> HIGH #> \"HIGH<\/i><\/span>\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/column_annotation_label.html","id":null,"dir":"Reference","previous_headings":"","what":"Get full label, useful for annotating plots — column_annotation_label","title":"Get full label, useful for annotating plots — column_annotation_label","text":"Get full label, useful annotating plots","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/column_annotation_label.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get full label, useful for annotating plots — column_annotation_label","text":"","code":"column_annotation_label(dataset, column, omit_raw_name = FALSE)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/column_annotation_label.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get full label, useful for annotating plots — column_annotation_label","text":"dataset (data.frame) dataset column (character) column get label omit_raw_name (logical) omits raw name square brackets label found","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/column_annotation_label.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get full label, useful for annotating plots — column_annotation_label","text":"\"Label [Column name]\" label exists, otherwise \"Column name\".","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/column_annotation_label.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get full label, useful for annotating plots — column_annotation_label","text":"","code":"data <- mtcars column_annotation_label(data, \"cyl\") #> [1] \"cyl\" attr(data[[\"cyl\"]], \"label\") <- \"Cylinder\" column_annotation_label(data, \"cyl\") #> [1] \"Cylinder [cyl]\" column_annotation_label(data, \"cyl\", omit_raw_name = TRUE) #> [1] \"Cylinder\" column_annotation_label(tmc_ex_adsl, \"ACTARM\") #> [1] \"Description of Actual Arm [ACTARM]\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/control_tte.html","id":null,"dir":"Reference","previous_headings":"","what":"Control Function for Time-To-Event teal Module — control_tte","title":"Control Function for Time-To-Event teal Module — control_tte","text":"Controls arguments Cox regression survival analysis results.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/control_tte.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Control Function for Time-To-Event teal Module — control_tte","text":"","code":"control_tte( surv_time = list(conf_level = 0.95, conf_type = \"plain\", quantiles = c(0.25, 0.75)), coxph = list(pval_method = \"log-rank\", ties = \"efron\", conf_level = 0.95), surv_timepoint = control_surv_timepoint(conf_level = 0.95, conf_type = c(\"plain\", \"none\", \"log\", \"log-log\")) )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/control_tte.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Control Function for Time-To-Event teal Module — control_tte","text":"surv_time (list) control parameters survfit model. See tern::control_surv_time() details. coxph (list) control parameters Cox-PH model. See tern::control_coxph() details. surv_timepoint (list) control parameters survfit model time point. See tern::control_surv_timepoint() details.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_des_filter.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert choices_selected to data_extract_spec with only filter_spec — cs_to_des_filter","title":"Convert choices_selected to data_extract_spec with only filter_spec — cs_to_des_filter","text":"Convert choices_selected data_extract_spec filter_spec","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_des_filter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert choices_selected to data_extract_spec with only filter_spec — cs_to_des_filter","text":"","code":"cs_to_des_filter( cs, dataname, multiple = FALSE, include_vars = FALSE, label = \"Filter by\" )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_des_filter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert choices_selected to data_extract_spec with only filter_spec — cs_to_des_filter","text":"cs (choices_selected) object transformed. See teal.transform::choices_selected() details. dataname (character) name data multiple (logical) Whether multiple values shall allowed shiny shiny::selectInput(). include_vars (flag) whether include filter variables fixed selection result. can useful preserving reuse rtables code e.g. label (character) Label print selection field. label, set NULL.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_des_filter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert choices_selected to data_extract_spec with only filter_spec — cs_to_des_filter","text":"(teal.transform::data_extract_spec())","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_des_select.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert choices_selected to data_extract_spec with only select_spec — cs_to_des_select","title":"Convert choices_selected to data_extract_spec with only select_spec — cs_to_des_select","text":"Convert choices_selected data_extract_spec select_spec","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_des_select.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert choices_selected to data_extract_spec with only select_spec — cs_to_des_select","text":"","code":"cs_to_des_select( cs, dataname, multiple = FALSE, ordered = FALSE, label = \"Select\" )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_des_select.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert choices_selected to data_extract_spec with only select_spec — cs_to_des_select","text":"cs (choices_selected) object transformed. See teal.transform::choices_selected() details. dataname (character) name data multiple (logical) Whether multiple values shall allowed shiny shiny::selectInput(). ordered (logical(1)) Flags whether selection order tracked. label (character) Label print selection field. label, set NULL.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_des_select.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert choices_selected to data_extract_spec with only select_spec — cs_to_des_select","text":"(teal.transform::data_extract_spec())","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_filter_spec.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert choices_selected to filter_spec — cs_to_filter_spec","title":"Convert choices_selected to filter_spec — cs_to_filter_spec","text":"Convert choices_selected filter_spec","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_filter_spec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert choices_selected to filter_spec — cs_to_filter_spec","text":"","code":"cs_to_filter_spec(cs, multiple = FALSE, label = \"Filter by\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_filter_spec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert choices_selected to filter_spec — cs_to_filter_spec","text":"cs (choices_selected) object transformed. See teal.transform::choices_selected() details. multiple (logical) Whether multiple values shall allowed shiny shiny::selectInput(). label (character) Label print selection field. label, set NULL.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_filter_spec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert choices_selected to filter_spec — cs_to_filter_spec","text":"(teal.transform::filter_spec())","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_select_spec.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert choices_selected to select_spec — cs_to_select_spec","title":"Convert choices_selected to select_spec — cs_to_select_spec","text":"Convert choices_selected select_spec","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_select_spec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert choices_selected to select_spec — cs_to_select_spec","text":"","code":"cs_to_select_spec(cs, multiple = FALSE, ordered = FALSE, label = \"Select\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_select_spec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert choices_selected to select_spec — cs_to_select_spec","text":"cs (choices_selected) object transformed. See teal.transform::choices_selected() details. multiple (logical) Whether multiple values shall allowed shiny shiny::selectInput(). ordered (logical(1)) Flags whether selection order tracked. label (character) Label print selection field. label, set NULL.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/cs_to_select_spec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert choices_selected to select_spec — cs_to_select_spec","text":"(select_spec)","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/default_total_label.html","id":null,"dir":"Reference","previous_headings":"","what":"Default string for total column label — default_total_label","title":"Default string for total column label — default_total_label","text":"default string used label \"total\" column. value used default value total_label argument throughout teal.modules.clinical package. specified module user via total_label argument, R environment options via set_default_total_label(), \"Patients\" used.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/default_total_label.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Default string for total column label — default_total_label","text":"","code":"default_total_label() set_default_total_label(total_label)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/default_total_label.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Default string for total column label — default_total_label","text":"total_label (string) Single string value set R environment options default label use \"total\" column. Use getOption(\"tmc_default_total_label\") check current value set R environment (defaults \"Patients\" set).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/default_total_label.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Default string for total column label — default_total_label","text":"default_total_label returns current value R environment option set \"tmc_default_total_label\", \"Patients\" otherwise. set_default_total_label return value.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/default_total_label.html","id":"functions","dir":"Reference","previous_headings":"","what":"Functions","title":"Default string for total column label — default_total_label","text":"default_total_label(): Getter default total column label. set_default_total_label(): Setter default total column label. Sets option \"tmc_default_total_label\" within R environment.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/default_total_label.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Default string for total column label — default_total_label","text":"","code":"# Default settings default_total_label() #> [1] \"All Patients\" getOption(\"tmc_default_total_label\") #> NULL # Set custom value set_default_total_label(\"All Patients\") # Settings after value has been set default_total_label() #> [1] \"All Patients\" getOption(\"tmc_default_total_label\") #> [1] \"All Patients\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/ex_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Simulated CDISC Data for Examples — ex_data","title":"Simulated CDISC Data for Examples — ex_data","text":"Simulated CDISC Data Examples","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/ex_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simulated CDISC Data for Examples — ex_data","text":"","code":"tmc_ex_adsl tmc_ex_adae tmc_ex_adaette tmc_ex_adcm tmc_ex_adeg tmc_ex_adex tmc_ex_adlb tmc_ex_admh tmc_ex_adqs tmc_ex_adrs tmc_ex_adtte tmc_ex_advs"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/ex_data.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Simulated CDISC Data for Examples — ex_data","text":"rds (data.frame) object class tbl_df (inherits tbl, data.frame) 200 rows 26 columns. object class tbl_df (inherits tbl, data.frame) 541 rows 51 columns. object class tbl_df (inherits tbl, data.frame) 1800 rows 35 columns. object class tbl_df (inherits tbl, data.frame) 512 rows 45 columns. object class tbl_df (inherits tbl, data.frame) 5200 rows 48 columns. object class tbl_df (inherits tbl, data.frame) 200 rows 37 columns. object class tbl_df (inherits tbl, data.frame) 3000 rows 58 columns. object class tbl_df (inherits tbl, data.frame) 1077 rows 33 columns. object class tbl_df (inherits tbl, data.frame) 7000 rows 36 columns. object class tbl_df (inherits tbl, data.frame) 1600 rows 34 columns. object class tbl_df (inherits tbl, data.frame) 1000 rows 34 columns. object class tbl_df (inherits tbl, data.frame) 8400 rows 34 columns.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/ex_data.html","id":"functions","dir":"Reference","previous_headings":"","what":"Functions","title":"Simulated CDISC Data for Examples — ex_data","text":"tmc_ex_adsl: ADSL data tmc_ex_adae: ADAE data tmc_ex_adaette: ADAETTE data tmc_ex_adcm: ADCM data tmc_ex_adeg: ADEG data tmc_ex_adex: ADEX data tmc_ex_adlb: ADLB data tmc_ex_admh: ADMH data tmc_ex_adqs: ADQS data tmc_ex_adrs: ADRS data tmc_ex_adtte: ADTTE data tmc_ex_advs: ADVS data","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/extract_input.html","id":null,"dir":"Reference","previous_headings":"","what":"Extracts html id for data_extract_ui — extract_input","title":"Extracts html id for data_extract_ui — extract_input","text":"data_extract_ui located extended html id. use ns(\"original id\") reference, extended specific suffixes.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/extract_input.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extracts html id for data_extract_ui — extract_input","text":"","code":"extract_input(varname, dataname, filter = FALSE)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/extract_input.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extracts html id for data_extract_ui — extract_input","text":"varname (character) original html id. retrieved ns(\"original id\") UI function session$ns(\"original id\")/\"original id\" server function. dataname (character)dataname data_extract input. might retrieved like data_extract_spec(...)[[1]]$dataname. filter (logical) optional, connected extract_data_spec objects passed filter argument","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/extract_input.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extracts html id for data_extract_ui — extract_input","text":"string","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/extract_input.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extracts html id for data_extract_ui — extract_input","text":"","code":"extract_input(\"ARM\", \"ADSL\") #> [1] \"ARM-dataset_ADSL_singleextract-select\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/facet_grid_formula.html","id":null,"dir":"Reference","previous_headings":"","what":"Facetting formula x_facet ~ y_facet — facet_grid_formula","title":"Facetting formula x_facet ~ y_facet — facet_grid_formula","text":"Replaces x_facet y_facet . empty character","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/facet_grid_formula.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Facetting formula x_facet ~ y_facet — facet_grid_formula","text":"","code":"facet_grid_formula(x_facet, y_facet)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/facet_grid_formula.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Facetting formula x_facet ~ y_facet — facet_grid_formula","text":"x_facet (character(1)) name x facet, empty, facet along x. y_facet (character(1)) name y facet, empty, facet along y.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/facet_grid_formula.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Facetting formula x_facet ~ y_facet — facet_grid_formula","text":"facet grid formula formula(x_facet ~ y_facet)","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/get_g_forest_obj_var_name.html","id":null,"dir":"Reference","previous_headings":"","what":"Utility function for extracting paramcd for forest plots — get_g_forest_obj_var_name","title":"Utility function for extracting paramcd for forest plots — get_g_forest_obj_var_name","text":"Utility function extracting paramcd forest plots","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/get_g_forest_obj_var_name.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Utility function for extracting paramcd for forest plots — get_g_forest_obj_var_name","text":"","code":"get_g_forest_obj_var_name(paramcd, input, filter_idx = 1)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/get_g_forest_obj_var_name.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Utility function for extracting paramcd for forest plots — get_g_forest_obj_var_name","text":"paramcd teal.transform::data_extract_spec() variable value designating studied parameter. input shiny app input filter_idx filter section index (default 1)","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/get_paramcd_label.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract the associated parameter value for paramcd — get_paramcd_label","title":"Extract the associated parameter value for paramcd — get_paramcd_label","text":"Utility function extracting parameter value associated paramcd value label. parameter value paramcd label, paramcd value returned. used generating title.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/get_paramcd_label.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract the associated parameter value for paramcd — get_paramcd_label","text":"","code":"get_paramcd_label(anl, paramcd)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/get_paramcd_label.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract the associated parameter value for paramcd — get_paramcd_label","text":"anl Analysis dataset paramcd teal.transform::data_extract_spec() variable value designating studied parameter.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/get_var_labels.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get variable labels — get_var_labels","text":"","code":"get_var_labels(datasets, dataname, vars)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/get_var_labels.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get variable labels — get_var_labels","text":"datasets (teal::FilteredData) Data built teal dataname (character) name dataset vars (character) Column names data","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/get_var_labels.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get variable labels — get_var_labels","text":"character variable labels.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/h_concat_expr.html","id":null,"dir":"Reference","previous_headings":"","what":"Expression Deparsing — h_concat_expr","title":"Expression Deparsing — h_concat_expr","text":"Deparse expression string.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/h_concat_expr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Expression Deparsing — h_concat_expr","text":"","code":"h_concat_expr(expr)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/h_concat_expr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Expression Deparsing — h_concat_expr","text":"expr (call) object can used .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/h_concat_expr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Expression Deparsing — h_concat_expr","text":"string.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/h_concat_expr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Expression Deparsing — h_concat_expr","text":"","code":"expr <- quote({ library(rtables) basic_table() %>% split_cols_by(var = \"ARMCD\") %>% test_proportion_diff( vars = \"rsp\", method = \"cmh\", variables = list(strata = \"strata\") ) %>% build_table(df = dta) }) h_concat_expr(expr) #> [1] \"{\\n library(rtables)\\n basic_table() %>% split_cols_by(var = \\\"ARMCD\\\") %>% test_proportion_diff(vars = \\\"rsp\\\", \\n method = \\\"cmh\\\", variables = list(strata = \\\"strata\\\")) %>% \\n build_table(df = dta)\\n}\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/is.cs_or_des.html","id":null,"dir":"Reference","previous_headings":"","what":"Whether object is of class teal.transform::choices_selected() — is.cs_or_des","title":"Whether object is of class teal.transform::choices_selected() — is.cs_or_des","text":"Whether object class teal.transform::choices_selected()","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/is.cs_or_des.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Whether object is of class teal.transform::choices_selected() — is.cs_or_des","text":"","code":"is.cs_or_des(x)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/is.cs_or_des.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Whether object is of class teal.transform::choices_selected() — is.cs_or_des","text":"x object checked","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/is.cs_or_des.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Whether object is of class teal.transform::choices_selected() — is.cs_or_des","text":"(logical)","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/make_barchart_simple_call.html","id":null,"dir":"Reference","previous_headings":"","what":"ggplot2 call to generate simple bar chart — make_barchart_simple_call","title":"ggplot2 call to generate simple bar chart — make_barchart_simple_call","text":"ggplot2 call generate simple bar chart","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/make_barchart_simple_call.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ggplot2 call to generate simple bar chart — make_barchart_simple_call","text":"","code":"make_barchart_simple_call( y_name, x_name = NULL, fill_name = NULL, x_facet_name = NULL, y_facet_name = NULL, label_bars = TRUE, barlayout = c(\"side_by_side\", \"stacked\"), flip_axis = FALSE, rotate_bar_labels = FALSE, rotate_x_label = FALSE, rotate_y_label = FALSE, expand_y_range = 0, facet_scales = \"free_x\", ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/make_barchart_simple_call.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ggplot2 call to generate simple bar chart — make_barchart_simple_call","text":"y_name (character NULL) name y-axis variable. x_name (character NULL) name x-axis variable. Defaults NULL dependent extract input can empty. fill_name (character NULL) name variable determine bar fill color. x_facet_name (character NULL) name variable use horizontal plot faceting. y_facet_name (character NULL) name variable use vertical plot faceting. label_bars (logical NULL) whether bars labeled. TRUE, label bar numbers also drawn text. barlayout (character NULL) type bar layout. Options \"stacked\" (default) \"side_by_side\". flip_axis (character NULL) whether flip plot axis. rotate_bar_labels (logical NULL) whether bar labels rotated 45 degrees. rotate_x_label (logical NULL) whether x-axis labels rotated 45 degrees. rotate_y_label (logical NULL) whether y-axis labels rotated 45 degrees. expand_y_range (numeric NULL) fraction y-axis range expand . facet_scales (character) value passed scales argument ggplot2::facet_grid(). Options fixed, free_x, free_y, free. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/make_barchart_simple_call.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ggplot2 call to generate simple bar chart — make_barchart_simple_call","text":"call produce ggplot object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/module_arguments.html","id":null,"dir":"Reference","previous_headings":"","what":"Standard Module Arguments — module_arguments","title":"Standard Module Arguments — module_arguments","text":"documentation function lists arguments teal modules used repeatedly express analysis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/module_arguments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standard Module Arguments — module_arguments","text":"arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. atirel (teal.transform::choices_selected()) object available choices preselected option ATIREL variable dataname. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. avalu_var (teal.transform::choices_selected()) object available choices preselected option analysis unit variable. avisit (teal.transform::choices_selected()) value analysis visit AVISIT interest. baseline_var (teal.transform::choices_selected()) object available choices preselected option variable values can used baseline_var. by_vars (teal.transform::choices_selected()) object available choices preselected option variable names used split summary rows. cmdecod (teal.transform::choices_selected()) object available choices preselected option CMDECOD variable dataname. cmindc (teal.transform::choices_selected()) object available choices preselected option CMINDC variable dataname. cmstdy (teal.transform::choices_selected()) object available choices preselected option CMSTDY variable dataname. cnsr_var (teal.transform::choices_selected()) object available choices preselected option censoring variable. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). cov_var (teal.transform::choices_selected()) object available choices preselected option covariates variables. dataname (character) analysis data used teal module. default_responses (list character) defines default codes response variable module per value paramcd. passed vector transmitted paramcd values. passed list must named contain arrays, name corresponding single value paramcd. array may contain default response values named arrays rsp default selected response values levels default level choices. fixed_symbol_size (logical) (TRUE), symbol size used plotting estimate. Otherwise, symbol size proportional sample size subgroup. font_size (numeric) numeric vector length 3 current, minimum maximum font size values. hlt (teal.transform::choices_selected()) name variable high level term events. id_var (teal.transform::choices_selected()) object specifying variable name subject id. interact_var (character) name variable interactions arm. interaction needed, default option NULL. interact_y (character) selected item interact_var column used select specific ANCOVA results interact_var discrete. interaction needed, default option FALSE. label (character) menu item label module teal app. llt (teal.transform::choices_selected()) name variable low level term events. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. pre_output (shiny.tag) optional, text placed output put output context. example title. strata_var (teal.transform::choices_selected()) names variables stratified analysis. summarize_vars (teal.transform::choices_selected()) names variables summarized. subgroup_var (teal.transform::choices_selected()) object available choices preselected option variable names can used default subgroups. time_points (teal.transform::choices_selected()) object available choices preselected option time points can used tern::surv_timepoint(). time_unit_var (teal.transform::choices_selected()) object available choices pre-selected option time unit variable. treatment_flag (teal.transform::choices_selected()) value indicating treatment records treatment_flag_var. treatment_flag_var (teal.transform::choices_selected()) treatment flag variable. useNA (character) whether missing data (NA) displayed level. visit_var (teal.transform::choices_selected()) object available choices preselected option variable names can used visit variable. Must factor dataname. worst_flag_indicator (teal.transform::choices_selected()) value indicating worst grade. worst_flag_var (teal.transform::choices_selected()) object available choices preselected option variable names can used worst flag variable. decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/module_arguments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standard Module Arguments — module_arguments","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/module_arguments.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Standard Module Arguments — module_arguments","text":"Although function just returns NULL two uses, teal module users provides documentation arguments commonly consistently used framework. developer adds single reference point import roxygen argument description : @inheritParams module_arguments Parameters identical descriptions & input types Standard Template Arguments section excluded reduce duplication module function inherits parameters corresponding template function.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/normalize_decorators.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert flat list of teal_transform_module to named lists — normalize_decorators","title":"Convert flat list of teal_transform_module to named lists — normalize_decorators","text":"Convert flat list teal_transform_module named lists","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/normalize_decorators.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert flat list of teal_transform_module to named lists — normalize_decorators","text":"","code":"normalize_decorators(decorators)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/normalize_decorators.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert flat list of teal_transform_module to named lists — normalize_decorators","text":"decorators (list teal_transformodules) normalize.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/normalize_decorators.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert flat list of teal_transform_module to named lists — normalize_decorators","text":"named list lists teal_transform_module objects.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/pipe_expr.html","id":null,"dir":"Reference","previous_headings":"","what":"Expressions as a Pipeline — pipe_expr","title":"Expressions as a Pipeline — pipe_expr","text":"Concatenate expressions single pipeline-flavor expression.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/pipe_expr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Expressions as a Pipeline — pipe_expr","text":"","code":"pipe_expr(exprs, pipe_str = \"%>%\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/pipe_expr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Expressions as a Pipeline — pipe_expr","text":"exprs (list call) expressions concatenate pipeline (%>%). pipe_str (character) character separates expressions.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/pipe_expr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Expressions as a Pipeline — pipe_expr","text":"call","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/pipe_expr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Expressions as a Pipeline — pipe_expr","text":"","code":"pipe_expr( list( expr1 = substitute(df), expr2 = substitute(head) ) ) #> df %>% head"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/prepare_arm.html","id":null,"dir":"Reference","previous_headings":"","what":"Expression: Arm Preparation — prepare_arm","title":"Expression: Arm Preparation — prepare_arm","text":"function generate standard expression pre-processing dataset teal module applications. especially interest preprocessing steps needs applied similarly several datasets (e.g. ADSL ADRS).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/prepare_arm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Expression: Arm Preparation — prepare_arm","text":"","code":"prepare_arm( dataname, arm_var, ref_arm, comp_arm, compare_arm = !is.null(ref_arm), ref_arm_val = paste(ref_arm, collapse = \"/\"), drop = TRUE )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/prepare_arm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Expression: Arm Preparation — prepare_arm","text":"dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. compare_arm (logical) triggers comparison study arms. ref_arm_val (character) replacement name reference level. drop (logical) drop unused variable levels.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/prepare_arm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Expression: Arm Preparation — prepare_arm","text":"call","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/prepare_arm.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Expression: Arm Preparation — prepare_arm","text":"teal.modules.clinical, user interface includes manipulation study arms. Classically: arm variable (e.g. ARM, ACTARM), reference arm (0 ), comparison arm (1 ) possibility combine comparison arms. Note arms compared , produced expression reduced optionally dropping non-represented levels arm. comparing arms, pre-processing includes three steps: Filtering dataset retain arms interest (reference comparison). Optional, one arm designated reference combined single level. reference explicitly reassigned non-represented levels arm dropped.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/prepare_arm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Expression: Arm Preparation — prepare_arm","text":"","code":"prepare_arm( dataname = \"adrs\", arm_var = \"ARMCD\", ref_arm = \"ARM A\", comp_arm = c(\"ARM B\", \"ARM C\") ) #> adrs %>% dplyr::filter(ARMCD %in% c(\"ARM A\", \"ARM B\", \"ARM C\")) %>% #> dplyr::mutate(ARMCD = stats::relevel(ARMCD, ref = \"ARM A\")) %>% #> dplyr::mutate(ARMCD = droplevels(ARMCD)) prepare_arm( dataname = \"adsl\", arm_var = \"ARMCD\", ref_arm = c(\"ARM B\", \"ARM C\"), comp_arm = \"ARM A\" ) #> adsl %>% dplyr::filter(ARMCD %in% c(\"ARM B\", \"ARM C\", \"ARM A\")) %>% #> dplyr::mutate(ARMCD = combine_levels(ARMCD, levels = c(\"ARM B\", #> \"ARM C\"), new_level = \"ARM B/ARM C\")) %>% dplyr::mutate(ARMCD = stats::relevel(ARMCD, #> ref = \"ARM B/ARM C\")) %>% dplyr::mutate(ARMCD = droplevels(ARMCD))"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/prepare_arm_levels.html","id":null,"dir":"Reference","previous_headings":"","what":"Expression: Prepare Arm Levels — prepare_arm_levels","title":"Expression: Prepare Arm Levels — prepare_arm_levels","text":"function generates standard expression pre-processing dataset arm levels used apply steps safety teal modules.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/prepare_arm_levels.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Expression: Prepare Arm Levels — prepare_arm_levels","text":"","code":"prepare_arm_levels(dataname, parentname, arm_var, drop_arm_levels = TRUE)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/prepare_arm_levels.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Expression: Prepare Arm Levels — prepare_arm_levels","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/prepare_arm_levels.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Expression: Prepare Arm Levels — prepare_arm_levels","text":"{ object. See base::Paren() details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/prepare_arm_levels.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Expression: Prepare Arm Levels — prepare_arm_levels","text":"","code":"prepare_arm_levels( dataname = \"adae\", parentname = \"adsl\", arm_var = \"ARMCD\", drop_arm_levels = TRUE ) #> { #> adae <- adae %>% dplyr::mutate(ARMCD = droplevels(ARMCD)) #> arm_levels <- levels(adae[[\"ARMCD\"]]) #> adsl <- adsl %>% dplyr::filter(ARMCD %in% arm_levels) #> adsl <- adsl %>% dplyr::mutate(ARMCD = droplevels(ARMCD)) #> } prepare_arm_levels( dataname = \"adae\", parentname = \"adsl\", arm_var = \"ARMCD\", drop_arm_levels = FALSE ) #> { #> adsl <- adsl %>% dplyr::mutate(ARMCD = droplevels(ARMCD)) #> arm_levels <- levels(adsl[[\"ARMCD\"]]) #> adae <- adae %>% dplyr::mutate(ARMCD = factor(ARMCD, levels = arm_levels)) #> }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/select_decorators.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset decorators based on the scope — select_decorators","title":"Subset decorators based on the scope — select_decorators","text":"default protected decorator name always included output, exists","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/select_decorators.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset decorators based on the scope — select_decorators","text":"","code":"select_decorators(decorators, scope)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/select_decorators.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subset decorators based on the scope — select_decorators","text":"decorators (named list) list decorators subset. scope (character) character vector decorator names include.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/select_decorators.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subset decorators based on the scope — select_decorators","text":"flat list decorators include. can empty list none scope exists decorators argument.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_choices.html","id":null,"dir":"Reference","previous_headings":"","what":"Split choices_selected objects with interactions into their component variables — split_choices","title":"Split choices_selected objects with interactions into their component variables — split_choices","text":"Split choices_selected objects interactions component variables","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_choices.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split choices_selected objects with interactions into their component variables — split_choices","text":"","code":"split_choices(x)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_choices.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split choices_selected objects with interactions into their component variables — split_choices","text":"x (choices_selected) object interaction terms","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_choices.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split choices_selected objects with interactions into their component variables — split_choices","text":"teal.transform::choices_selected() object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_choices.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Split choices_selected objects with interactions into their component variables — split_choices","text":"uses regex \\\\*|: perform split.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_choices.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split choices_selected objects with interactions into their component variables — split_choices","text":"","code":"split_choices(choices_selected(choices = c(\"x:y\", \"a*b\"), selected = all_choices())) #> $choices #> [1] \"x\" \"y\" \"a\" \"b\" #> #> $selected #> [1] \"x\" \"y\" \"a\" \"b\" #> #> $fixed #> [1] FALSE #> #> attr(,\"class\") #> [1] \"choices_selected\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_col_expr.html","id":null,"dir":"Reference","previous_headings":"","what":"Split-Column Expression — split_col_expr","title":"Split-Column Expression — split_col_expr","text":"Renders expression column split rtables depending : expected arm comparison expected arm combination","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_col_expr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split-Column Expression — split_col_expr","text":"","code":"split_col_expr(compare, combine, ref, arm_var)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_col_expr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split-Column Expression — split_col_expr","text":"compare (logical) TRUE reference level included. combine (logical) TRUE group combination included. ref (character) reference level (used combine = TRUE). arm_var (character) arm grouping variable name.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_col_expr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split-Column Expression — split_col_expr","text":"call","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_col_expr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split-Column Expression — split_col_expr","text":"","code":"split_col_expr( compare = TRUE, combine = FALSE, ref = \"ARM A\", arm_var = \"ARMCD\" ) #> rtables::split_cols_by(var = \"ARMCD\", ref_group = \"ARM A\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_interactions.html","id":null,"dir":"Reference","previous_headings":"","what":"Split interaction terms into their component variables — split_interactions","title":"Split interaction terms into their component variables — split_interactions","text":"Split interaction terms component variables","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_interactions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split interaction terms into their component variables — split_interactions","text":"","code":"split_interactions(x, by = \"\\\\*|:\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_interactions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split interaction terms into their component variables — split_interactions","text":"x (character) string representing interaction usually form x:y x*y. (character) regex split interaction term .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_interactions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split interaction terms into their component variables — split_interactions","text":"vector strings element component variable extracted interaction term x.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/split_interactions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split interaction terms into their component variables — split_interactions","text":"","code":"split_interactions(\"x:y\") #> [1] \"x\" \"y\" split_interactions(\"x*y\") #> [1] \"x\" \"y\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/srv_decorate_teal_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrappers around srv_transform_teal_data that allows to decorate the data — srv_decorate_teal_data","title":"Wrappers around srv_transform_teal_data that allows to decorate the data — srv_decorate_teal_data","text":"Wrappers around srv_transform_teal_data allows decorate data","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/srv_decorate_teal_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrappers around srv_transform_teal_data that allows to decorate the data — srv_decorate_teal_data","text":"","code":"srv_decorate_teal_data(id, data, decorators, expr, expr_is_reactive = FALSE) ui_decorate_teal_data(id, decorators, ...)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/srv_decorate_teal_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrappers around srv_transform_teal_data that allows to decorate the data — srv_decorate_teal_data","text":"id (character(1)) Module id data (reactive teal_data) expr (expression reactive) evaluate output decoration. expression must inline code. See within() Default NULL evaluate appending code. expr_is_reactive (logical(1)) whether expr reactive expression skips defusing argument.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/srv_decorate_teal_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Wrappers around srv_transform_teal_data that allows to decorate the data — srv_decorate_teal_data","text":"srv_decorate_teal_data wrapper around srv_transform_teal_data allows decorate data additional expressions. original teal_data object error state, show error first. ui_decorate_teal_data wrapper around ui_transform_teal_data.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/substitute_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Substitute Names in a Quoted Expression — substitute_names","title":"Substitute Names in a Quoted Expression — substitute_names","text":"function substitutes names left- right-hand sides quoted expression. addition can also standard substitutions right-hand side.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/substitute_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Substitute Names in a Quoted Expression — substitute_names","text":"","code":"substitute_names(expr, names, others = list()) h_subst_lhs_names(qexpr, names) substitute_lhs_names(qexpr, names) substitute_rhs(qexpr, env)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/substitute_names.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Substitute Names in a Quoted Expression — substitute_names","text":"expr (language) expression. names (named list name) requested name substitutions. others (named list) requested substitutions happen right-hand side. qexpr (language) quoted expression. env (environment list) requested variable substitutions.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/substitute_names.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Substitute Names in a Quoted Expression — substitute_names","text":"modified expression.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/substitute_names.html","id":"functions","dir":"Reference","previous_headings":"","what":"Functions","title":"Substitute Names in a Quoted Expression — substitute_names","text":"h_subst_lhs_names(): Helper function just substitute top-level names left-hand side quoted expression. substitute_lhs_names(): recursively substitutes names left-hand sides quoted expression. substitute_rhs(): substitutes right-hand side quoted expression. Note just synonym substitute_q().","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/substitute_q.html","id":null,"dir":"Reference","previous_headings":"","what":"Substitute in Quoted Expressions — substitute_q","title":"Substitute in Quoted Expressions — substitute_q","text":"version substitute needed substitute() evaluate first argument, often useful able modify quoted expression.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/substitute_q.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Substitute in Quoted Expressions — substitute_q","text":"","code":"substitute_q(qexpr, env)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/substitute_q.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Substitute in Quoted Expressions — substitute_q","text":"qexpr (language) quoted expression. env (environment list) requested variable substitutions.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/substitute_q.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Substitute in Quoted Expressions — substitute_q","text":"modified expression.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/substitute_q.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Substitute in Quoted Expressions — substitute_q","text":"simplified package pryr avoid another dependency.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/teal.modules.clinical-package.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Modules for Standard Clinical Outputs — teal.modules.clinical-package","title":"teal Modules for Standard Clinical Outputs — teal.modules.clinical-package","text":"Provides teal modules standard clinical trials outputs. teal modules add encoding panel interactively change encodings within teal.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/teal.modules.clinical-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"teal Modules for Standard Clinical Outputs — teal.modules.clinical-package","text":"Maintainer: Joe Zhu joe.zhu@roche.com Authors: Jana Stoilova jana.stoilova@roche.com Davide Garolini davide.garolini@roche.com Emily de la Rua emily.de_la_rua@contractors.roche.com Abinaya Yogasekaram abinaya.yogasekaram@contractors.roche.com Mahmoud Hallal mahmoud.hallal@roche.com Dawid Kaledkowski dawid.kaledkowski@roche.com Rosemary Li li.yaqiong@gene.com Heng Wang wang.heng@gene.com Pawel Rucki pawel.rucki@roche.com Nikolas Burkoff Konrad Pagacz contributors: Vaakesan Sundrelingam [contributor] Francois Collin [contributor] Imanol Zubizarreta [contributor] F. Hoffmann-La Roche AG [copyright holder, funder]","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_a_gee.html","id":null,"dir":"Reference","previous_headings":"","what":"Template for Generalized Estimating Equations (GEE) analysis module — template_a_gee","title":"Template for Generalized Estimating Equations (GEE) analysis module — template_a_gee","text":"Creates valid expression generate analysis table using Generalized Estimating Equations (GEE).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_a_gee.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template for Generalized Estimating Equations (GEE) analysis module — template_a_gee","text":"","code":"template_a_gee( output_table, data_model_fit = \"ANL\", dataname_lsmeans = \"ANL_ADSL\", input_arm_var = \"ARM\", ref_group = \"A: Drug X\", aval_var, id_var, arm_var, visit_var, split_covariates, cor_struct, conf_level = 0.95, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_a_gee.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template for Generalized Estimating Equations (GEE) analysis module — template_a_gee","text":"output_table (character) type output table (\"t_gee_cov\", \"t_gee_coef\", \"t_gee_lsmeans\"). data_model_fit (character) dataset used fit model tern.gee::fit_gee(). dataname_lsmeans (character) dataset used alt_counts_df argument rtables::build_table(). aval_var (character) name analysis value variable. id_var (character) variable name subject id. arm_var (character) variable names can used arm_var. visit_var (character) variable names can used visit variable. Must factor dataname. split_covariates (character) vector names variables use covariates tern.gee::vars_gee(). cor_struct (character) assumed correlation structure tern.gee::fit_gee. conf_level (numeric) value confidence level within range (0, 1). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_a_gee.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template for Generalized Estimating Equations (GEE) analysis module — template_a_gee","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_abnormality.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Abnormality Summary Table — template_abnormality","title":"Template: Abnormality Summary Table — template_abnormality","text":"Creates valid expression generate table summarize abnormality.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_abnormality.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Abnormality Summary Table — template_abnormality","text":"","code":"template_abnormality( parentname, dataname, arm_var, id_var = \"USUBJID\", by_vars, abnormal = list(low = c(\"LOW\", \"LOW LOW\"), high = c(\"HIGH\", \"HIGH HIGH\")), grade = \"ANRIND\", baseline_var = \"BNRIND\", treatment_flag_var = \"ONTRTFL\", treatment_flag = \"Y\", add_total = FALSE, total_label = default_total_label(), exclude_base_abn = FALSE, drop_arm_levels = TRUE, na_level = default_na_str(), basic_table_args = teal.widgets::basic_table_args(), tbl_title )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_abnormality.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Abnormality Summary Table — template_abnormality","text":"parentname (character) parent analysis data used teal module, usually refers ADSL. dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. id_var (character) variable name subject id. by_vars (character) variable names used split summary rows. abnormal (named list) indicating abnormality direction grades. grade (character) name variable used specify abnormality grade. Variable must factor. baseline_var (character) name variable specifying baseline abnormality grade. treatment_flag_var (character) name treatment flag variable. treatment_flag (character) name value indicating treatment records treatment_flag_var. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). exclude_base_abn (logical) whether exclude patients abnormal values baseline. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. na_level (character) NA level input dataset, defaults \"\". basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). tbl_title (character) Title label variables bars","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_abnormality.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Abnormality Summary Table — template_abnormality","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_abnormality_by_worst_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Laboratory test results with highest grade post-baseline — template_abnormality_by_worst_grade","title":"Template: Laboratory test results with highest grade post-baseline — template_abnormality_by_worst_grade","text":"Creates valid expression generate table summarize abnormality grade.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_abnormality_by_worst_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Laboratory test results with highest grade post-baseline — template_abnormality_by_worst_grade","text":"","code":"template_abnormality_by_worst_grade( parentname, dataname, arm_var, id_var = \"USUBJID\", paramcd = \"PARAMCD\", atoxgr_var = \"ATOXGR\", worst_high_flag_var = \"WGRHIFL\", worst_low_flag_var = \"WGRLOFL\", worst_flag_indicator = \"Y\", add_total = FALSE, total_label = default_total_label(), drop_arm_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_abnormality_by_worst_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Laboratory test results with highest grade post-baseline — template_abnormality_by_worst_grade","text":"parentname (character) parent analysis data used teal module, usually refers ADSL. dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. id_var (character) variable name subject id. paramcd (character) name parameter code variable. atoxgr_var (character) name variable indicating Analysis Toxicity Grade. worst_high_flag_var (character) name variable indicating Worst High Grade flag worst_low_flag_var (character) name variable indicating Worst Low Grade flag worst_flag_indicator (character) flag value indicating worst grade. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_abnormality_by_worst_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Laboratory test results with highest grade post-baseline — template_abnormality_by_worst_grade","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_adverse_events.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Adverse Events Table and Plot — template_adverse_events","title":"Template: Patient Profile Adverse Events Table and Plot — template_adverse_events","text":"Creates valid expression generate adverse events table ggplot2::ggplot() plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_adverse_events.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Adverse Events Table and Plot — template_adverse_events","text":"","code":"template_adverse_events( dataname = \"ANL\", aeterm = \"AETERM\", tox_grade = \"AETOXGR\", causality = \"AEREL\", outcome = \"AEOUT\", action = \"AEACN\", time = \"ASTDY\", decod = NULL, patient_id, font_size = 12L, ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_adverse_events.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Adverse Events Table and Plot — template_adverse_events","text":"dataname (character) analysis data used teal module. aeterm (character) name reported term adverse event variable. tox_grade (character) name standard toxicity grade variable. causality (character) name causality variable. outcome (character) name outcome adverse event variable. action (character) name action taken study treatment variable. time (character) name study day start adverse event variable. decod (character) name dictionary derived term variable. patient_id (character) patient ID. font_size (numeric) font size value. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_adverse_events.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Adverse Events Table and Plot — template_adverse_events","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_ancova.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: ANCOVA Summary — template_ancova","title":"Template: ANCOVA Summary — template_ancova","text":"Creates valid expression generate analysis variance summary table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_ancova.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: ANCOVA Summary — template_ancova","text":"","code":"template_ancova( dataname = \"ANL\", parentname = \"ADSL\", arm_var, ref_arm = NULL, comp_arm = NULL, combine_comp_arms = FALSE, aval_var, label_aval = NULL, cov_var, include_interact = FALSE, interact_var = NULL, interact_y = FALSE, paramcd_levels = \"\", paramcd_var = \"PARAMCD\", label_paramcd = NULL, visit_levels = \"\", visit_var = \"AVISIT\", conf_level = 0.95, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_ancova.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: ANCOVA Summary — template_ancova","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. combine_comp_arms (logical) triggers combination comparison arms. aval_var (character) name analysis value variable. label_aval (character) label value variable used title rendering. cov_var (character) names covariates variables. include_interact (logical) whether interaction term included model. interact_var (character) name variable interactions arm. interaction needed, default option NULL. interact_y (character) selected item interact_var column used select specific ANCOVA results. interaction needed, default option FALSE. paramcd_levels (character) variable levels studied parameter. paramcd_var (character) variable name studied parameter. label_paramcd (character) variable label used title rendering. visit_levels (character) variable levels studied visits. visit_var (character) variable names can used visit variable. Must factor dataname. conf_level (numeric) value confidence level within range (0, 1). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_ancova.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: ANCOVA Summary — template_ancova","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_arguments.html","id":null,"dir":"Reference","previous_headings":"","what":"Standard Template Arguments — template_arguments","title":"Standard Template Arguments — template_arguments","text":"documentation function lists arguments teal module templates used repeatedly express analysis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_arguments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standard Template Arguments — template_arguments","text":"add_total (logical) whether include column total number patients. anl_name (character) analysis data used teal module. arm_var (character) variable names can used arm_var. atirel (character) name time relation medication variable. aval Please use aval_var argument instead. avalu Please use avalu_var argument instead. avalu_var (character) name analysis value unit variable. aval_var (character) name analysis value variable. baseline_var (character) name variable baseline values analysis variable. base_var Please use baseline_var argument instead. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). by_vars (character) variable names used split summary rows. cmdecod (character) name standardized medication name variable. cmindc (character) name indication variable. cmstdy (character) name study relative day start medication variable. cnsr_var (character) name censoring variable. combine_comp_arms (logical) triggers combination comparison arms. compare_arm (logical) triggers comparison study arms. comp_arm (character) level comparison arm case arm comparison. conf_level (numeric) value confidence level within range (0, 1). control (list) list settings analysis. cov_var (character) names covariates variables. dataname (character) analysis data used teal module. denominator (character) chooses percentages calculated. option N, reference population column total used denominator. option n, number non-missing records row column intersection used denominator. omit chosen, percentage omitted. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. event_type (character) type event summarized (e.g. adverse event, treatment). Default \"event\". font_size (numeric) font size value. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). hlt (character) name variable high level term events. id_var (character) variable name subject id. include_interact (logical) whether interaction term included model. label_hlt (string) label hlt variable dataname. label extracted module. label_llt (string) label llt variable dataname. label extracted module. llt (character) name variable low level term events. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). na.rm (logical) whether NA values removed prior analysis. numeric_stats (character) names statistics display numeric summary variables. Available statistics n, mean_sd, mean_ci, median, median_ci, quantiles, range, geom_mean. paramcd (character) name parameter code variable. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_id (character) patient ID. prune_diff (number) threshold use trimming table using criteria difference rates two columns. prune_freq (number) threshold use trimming table using event incidence rate column. ref_arm (character) level reference arm case arm comparison. sort_criteria (character) sort final table. Default option freq_desc sorts column sort_freq_col decreasing number patients event. Alternative option alpha sorts events alphabetically. strata_var (character) names variables stratified analysis. subgroup_var (character) variable names can used subgroups. sum_vars (character) names variables summarized. time_points (character) time points can used tern::surv_timepoint(). time_unit_var (character) name variable representing time units. title (character) title output. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). treatment_flag (character) name value indicating treatment records treatment_flag_var. treatment_flag_var (character) name treatment flag variable. useNA (character) whether missing data (NA) displayed level. var_labels (named character) optional variable labels relabeling analysis variables. visit_var (character) variable names can used visit variable. Must factor dataname. worst_flag_indicator (character) value indicating worst grade. worst_flag_var (character) name worst flag variable.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_arguments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standard Template Arguments — template_arguments","text":"list expressions generate table plot object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_arguments.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Standard Template Arguments — template_arguments","text":"Although function just returns NULL two uses, teal module users provides documentation arguments commonly consistently used framework. developer adds single reference point import roxygen argument description : @inheritParams template_arguments","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_basic_info.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Basic Info — template_basic_info","title":"Template: Patient Profile Basic Info — template_basic_info","text":"Creates valid expression generate patient profile basic info report using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_basic_info.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Basic Info — template_basic_info","text":"","code":"template_basic_info(dataname = \"ANL\", vars, patient_id = NULL)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_basic_info.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Basic Info — template_basic_info","text":"dataname (character) analysis data used teal module. vars (character) names variables shown table. patient_id (character) patient ID.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_basic_info.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Basic Info — template_basic_info","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_binary_outcome.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Binary Outcome — template_binary_outcome","title":"Template: Binary Outcome — template_binary_outcome","text":"Creates valid expression generate binary outcome analysis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_binary_outcome.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Binary Outcome — template_binary_outcome","text":"","code":"template_binary_outcome( dataname, parentname, arm_var, paramcd, ref_arm = NULL, comp_arm = NULL, compare_arm = FALSE, combine_comp_arms = FALSE, aval_var = \"AVALC\", show_rsp_cat = TRUE, responder_val = c(\"Complete Response (CR)\", \"Partial Response (PR)\"), responder_val_levels = responder_val, control = list(global = list(method = \"waldcc\", conf_level = 0.95), unstrat = list(method_ci = \"waldcc\", method_test = \"schouten\", odds = TRUE), strat = list(method_ci = \"cmh\", method_test = \"cmh\", strat = NULL)), add_total = FALSE, total_label = default_total_label(), na_level = default_na_str(), basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_binary_outcome.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Binary Outcome — template_binary_outcome","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. paramcd (character) response parameter value use table title. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. compare_arm (logical) triggers comparison study arms. combine_comp_arms (logical) triggers combination comparison arms. aval_var (character) name analysis value variable. show_rsp_cat (logical) display multinomial response estimations. responder_val (character) short label observations translate AVALC responder/non-responder. responder_val_levels (character) levels responses shown multinomial response estimations. control (list) list settings analysis. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_binary_outcome.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Binary Outcome — template_binary_outcome","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_coxreg_m.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Multi-Variable Cox Regression — template_coxreg_m","title":"Template: Multi-Variable Cox Regression — template_coxreg_m","text":"Creates valid expression generate multi-variable Cox regression analysis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_coxreg_m.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Multi-Variable Cox Regression — template_coxreg_m","text":"","code":"template_coxreg_m( dataname, cov_var, arm_var, cnsr_var, aval_var, ref_arm, comp_arm, paramcd, at = list(), strata_var = NULL, combine_comp_arms = FALSE, control = control_coxreg(), na_level = default_na_str(), basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_coxreg_m.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Multi-Variable Cox Regression — template_coxreg_m","text":"dataname (character) analysis data used teal module. cov_var (character) names covariates variables. arm_var (character) variable names can used arm_var. cnsr_var (character) name censoring variable. aval_var (character) name analysis value variable. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. paramcd (character) name parameter code variable. (list numeric) candidate covariate numeric type variable, use specify value covariate effect estimated. strata_var (character) names variables stratified analysis. combine_comp_arms (logical) triggers combination comparison arms. control (list) list settings analysis (see tern::control_coxreg()). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_coxreg_m.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Multi-Variable Cox Regression — template_coxreg_m","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_coxreg_u.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Univariable Cox Regression — template_coxreg_u","title":"Template: Univariable Cox Regression — template_coxreg_u","text":"Creates valid expression generate univariable Cox regression analysis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_coxreg_u.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Univariable Cox Regression — template_coxreg_u","text":"","code":"template_coxreg_u( dataname, cov_var, arm_var, cnsr_var, aval_var, ref_arm, comp_arm, paramcd, at = list(), strata_var = NULL, combine_comp_arms = FALSE, control = control_coxreg(), na_level = default_na_str(), append = FALSE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_coxreg_u.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Univariable Cox Regression — template_coxreg_u","text":"dataname (character) analysis data used teal module. cov_var (character) names covariates variables. arm_var (character) variable names can used arm_var. cnsr_var (character) name censoring variable. aval_var (character) name analysis value variable. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. paramcd (character) name parameter code variable. (list numeric) candidate covariate numeric type variable, use specify value covariate effect estimated. strata_var (character) names variables stratified analysis. combine_comp_arms (logical) triggers combination comparison arms. control (list) list settings analysis (see tern::control_coxreg()). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). append (logical) whether result appended previous one. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_coxreg_u.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Univariable Cox Regression — template_coxreg_u","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Events by Term — template_events","title":"Template: Events by Term — template_events","text":"Creates valid expression generate table events term.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Events by Term — template_events","text":"","code":"template_events( dataname, parentname, arm_var, hlt, llt, label_hlt = NULL, label_llt = NULL, add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), event_type = \"event\", sort_criteria = c(\"freq_desc\", \"alpha\"), sort_freq_col = total_label, prune_freq = 0, prune_diff = 0, drop_arm_levels = TRUE, incl_overall_sum = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Events by Term — template_events","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. hlt (character) name variable high level term events. llt (character) name variable low level term events. label_hlt (string) label hlt variable dataname. label extracted module. label_llt (string) label llt variable dataname. label extracted module. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). event_type (character) type event summarized (e.g. adverse event, treatment). Default \"event\". sort_criteria (character) sort final table. Default option freq_desc sorts column sort_freq_col decreasing number patients event. Alternative option alpha sorts events alphabetically. sort_freq_col (character) column sort frequency sort_criteria set freq_desc. prune_freq (number) threshold use trimming table using event incidence rate column. prune_diff (number) threshold use trimming table using criteria difference rates two columns. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. incl_overall_sum (flag) whether two rows summarize overall number adverse events included top table. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Events by Term — template_events","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_by_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Events by Grade — template_events_by_grade","title":"Template: Events by Grade — template_events_by_grade","text":"Creates valid expression generate table summarize events grade.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_by_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Events by Grade — template_events_by_grade","text":"","code":"template_events_by_grade( dataname, parentname, arm_var, id = \"\", hlt, llt, label_hlt = NULL, label_llt = NULL, grade, label_grade = NULL, prune_freq = 0, prune_diff = 0, add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), drop_arm_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_by_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Events by Grade — template_events_by_grade","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. id (character) unique identifier patients datasets, default \"USUBJID\". hlt (character) name variable high level term events. llt (character) name variable low level term events. label_hlt (string) label hlt variable dataname. label extracted module. label_llt (string) label llt variable dataname. label extracted module. grade (character) name severity level variable. label_grade (string) label grade variable dataname. label extracted module. prune_freq (number) threshold use trimming table using event incidence rate column. prune_diff (number) threshold use trimming table using criteria difference rates two columns. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_by_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Events by Grade — template_events_by_grade","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_col_by_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Adverse Events Grouped by Grade with Threshold — template_events_col_by_grade","title":"Template: Adverse Events Grouped by Grade with Threshold — template_events_col_by_grade","text":"Creates valid expression generate table summarize adverse events grouped grade.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_col_by_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Adverse Events Grouped by Grade with Threshold — template_events_col_by_grade","text":"","code":"template_events_col_by_grade( dataname, parentname, arm_var, grading_groups = list(`Any Grade (%)` = c(\"1\", \"2\", \"3\", \"4\", \"5\"), `Grade 1-2 (%)` = c(\"1\", \"2\"), `Grade 3-4 (%)` = c(\"3\", \"4\"), `Grade 5 (%)` = \"5\"), add_total = TRUE, total_label = default_total_label(), id = \"USUBJID\", hlt, llt, label_hlt = NULL, label_llt = NULL, grade = \"AETOXGR\", label_grade = NULL, prune_freq = 0.1, prune_diff = 0, na_level = default_na_str(), drop_arm_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_col_by_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Adverse Events Grouped by Grade with Threshold — template_events_col_by_grade","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. grading_groups (list) named list grading groups. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). id (character) name variable uniquely identify patients datasets. hlt (character) name variable high level term events. llt (character) name variable low level term events. label_hlt (string) label hlt variable dataname. label extracted module. label_llt (string) label llt variable dataname. label extracted module. grade (character) name grade variable base grading_groups . label_grade (character) label grade variable dataname. prune_freq (number) threshold use trimming table using event incidence rate column. prune_diff (number) threshold use trimming table using criteria difference rates two columns. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_col_by_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Adverse Events Grouped by Grade with Threshold — template_events_col_by_grade","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_patyear.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Event Rates Adjusted for Patient-Years — template_events_patyear","title":"Template: Event Rates Adjusted for Patient-Years — template_events_patyear","text":"Creates valid expression generate table event rates adjusted patient-years.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_patyear.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Event Rates Adjusted for Patient-Years — template_events_patyear","text":"","code":"template_events_patyear( dataname, parentname, arm_var, events_var, label_paramcd, aval_var = \"AVAL\", add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), control = control_incidence_rate(), drop_arm_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_patyear.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Event Rates Adjusted for Patient-Years — template_events_patyear","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. events_var (character) name variable number observed events. label_paramcd (character)paramcd variable text use table title. aval_var (character) name analysis value variable. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). control (list) list settings analysis. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_patyear.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Event Rates Adjusted for Patient-Years — template_events_patyear","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_summary.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Adverse Events Summary — template_events_summary","title":"Template: Adverse Events Summary — template_events_summary","text":"Creates valid expression generate adverse events summary table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_summary.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Adverse Events Summary — template_events_summary","text":"","code":"template_events_summary( anl_name, parentname, arm_var, dthfl_var = \"DTHFL\", dcsreas_var = \"DCSREAS\", flag_var_anl = NULL, flag_var_aesi = NULL, aeseq_var = \"AESEQ\", llt = \"AEDECOD\", add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), count_dth = TRUE, count_wd = TRUE, count_subj = TRUE, count_pt = TRUE, count_events = TRUE )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_summary.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Adverse Events Summary — template_events_summary","text":"anl_name (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. dthfl_var (character) name variable subject death flag parentname. Records \"Y\" summarized table row \"Total number deaths\". dcsreas_var (character) name variable study discontinuation reason parentname. Records \"ADVERSE EVENTS\" summarized table row \"Total number patients withdrawn study due AE\". flag_var_anl (character) name flag variable dataset used count adverse event sub-groups (e.g. Serious events, Related events, etc.). Variable labels used table row names exist. flag_var_aesi (character) name flag variable dataset used count adverse event special interest groups. flag variables must type logical. Variable labels used table row names exist. aeseq_var (character) name variable adverse events sequence number dataset. Used counting total number events. llt (character) name variable low level term events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). count_dth (logical) whether show count total deaths (based dthfl_var). Defaults TRUE. count_wd (logical) whether show count patients withdrawn study due adverse event (based dcsreas_var). Defaults TRUE. count_subj (logical) whether show count unique subjects (based USUBJID). applies event flag variables provided. count_pt (logical) whether show count unique preferred terms (based llt). applies event flag variables provided. count_events (logical) whether show count events (based aeseq_var). applies event flag variables provided.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_events_summary.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Adverse Events Summary — template_events_summary","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_exposure.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Exposure Table for Risk management plan — template_exposure","title":"Template: Exposure Table for Risk management plan — template_exposure","text":"Creates valid expression generate exposure table risk management plan.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_exposure.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Exposure Table for Risk management plan — template_exposure","text":"","code":"template_exposure( parentname, dataname, id_var, paramcd, paramcd_label = NULL, row_by_var, col_by_var = NULL, add_total = FALSE, total_label = \"Total\", add_total_row = TRUE, total_row_label = \"Total number of patients and patient time*\", drop_levels = TRUE, na_level = default_na_str(), aval_var, avalu_var, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_exposure.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Exposure Table for Risk management plan — template_exposure","text":"parentname (character) parent analysis data used teal module, usually refers ADSL. dataname (character) analysis data used teal module. id_var (character) variable name subject id. paramcd (character) name parameter code variable. paramcd_label (character) column dataname dataset value used label argument paramcd. row_by_var (character) variable name used split values rows. col_by_var (character) variable name used split values columns. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). add_total_row (flag) whether \"total\" level added others includes levels constitute split. custom label can set level via total_row_label argument. total_row_label (character) string display total row label row enabled (see add_total_row). drop_levels (flag) whether empty rows removed table. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). aval_var (character) name analysis value variable. avalu_var (character) name analysis value unit variable. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_exposure.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Exposure Table for Risk management plan — template_exposure","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_fit_mmrm.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm","title":"Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm","text":"Creates valid expression generate analysis tables plots Mixed Model Repeated Measurements.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_fit_mmrm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm","text":"","code":"template_fit_mmrm( parentname, dataname, aval_var, arm_var, ref_arm, comp_arm = NULL, combine_comp_arms = FALSE, id_var, visit_var, cov_var, conf_level = 0.95, method = \"Satterthwaite\", cor_struct = \"unstructured\", weights_emmeans = \"proportional\", parallel = FALSE ) template_mmrm_tables( parentname, dataname, fit_name, arm_var, ref_arm, visit_var, paramcd, show_relative = c(\"increase\", \"reduction\", \"none\"), table_type = \"t_mmrm_cov\", total_label = default_total_label(), basic_table_args = teal.widgets::basic_table_args() ) template_mmrm_plots( fit_name, lsmeans_plot = list(select = c(\"estimates\", \"contrasts\"), width = 0.6, show_pval = FALSE), diagnostic_plot = list(type = \"fit-residual\", z_threshold = NULL), ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_fit_mmrm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm","text":"parentname (character) parent analysis data used teal module, usually refers ADSL. dataname (character) analysis data used teal module. aval_var (character) name analysis value variable. arm_var (character) variable names can used arm_var. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. combine_comp_arms (logical) triggers combination comparison arms. id_var (character) variable name subject id. visit_var (character) variable names can used visit variable. Must factor dataname. cov_var (character) names covariates variables. conf_level (numeric) value confidence level within range (0, 1). method (string) string specifying adjustment method. cor_struct (string) string specifying correlation structure, defaults \"unstructured\". See tern.mmrm::build_formula() options. weights_emmeans argument emmeans::emmeans(), \"proportional\" default. parallel (flag) flag controls whether optimizer search can use available free cores machine (default). fit_name (string) name fitted MMRM object. paramcd (character) name parameter code variable. show_relative (string) \"reduction\" (control - treatment, default) \"increase\" (treatment - control) shown relative change baseline. table_type (string) type table output. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). lsmeans_plot (named list) list controls LS means plot. See tern.mmrm::g_mmrm_lsmeans(). diagnostic_plot (named list) list controls diagnostic_plot. See tern.mmrm::g_mmrm_diagnostic(). ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_fit_mmrm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm","text":"list expressions generate table plot object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_fit_mmrm.html","id":"functions","dir":"Reference","previous_headings":"","what":"Functions","title":"Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm","text":"template_mmrm_tables(): Creates valid expressions generate MMRM LS means, covariance matrix, fixed effects, diagnostic tables. template_mmrm_plots(): Creates valid expressions generate MMRM LS means diagnostic plots.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_forest_rsp.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Response Forest Plot — template_forest_rsp","title":"Template: Response Forest Plot — template_forest_rsp","text":"Creates valid expression generate response forest plot.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_forest_rsp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Response Forest Plot — template_forest_rsp","text":"","code":"template_forest_rsp( dataname = \"ANL\", parentname = \"ADSL\", arm_var, ref_arm = NULL, comp_arm = NULL, obj_var_name = \"\", aval_var = \"AVALC\", responders = c(\"CR\", \"PR\"), subgroup_var, strata_var = NULL, stats = c(\"n_tot\", \"n\", \"n_rsp\", \"prop\", \"or\", \"ci\"), riskdiff = NULL, conf_level = 0.95, col_symbol_size = NULL, rel_width_forest = 0.25, font_size = 15, ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_forest_rsp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Response Forest Plot — template_forest_rsp","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. obj_var_name (character) additional text append table title. aval_var (character) name analysis value variable. responders (character) values aval_var considered responders. subgroup_var (character) variable names can used subgroups. strata_var (character) names variables stratified analysis. stats (character) names statistics reported among: n: Total number observations per group. n_rsp: Number responders per group. prop: Proportion responders. n_tot: Total number observations. : Odds ratio. ci : Confidence interval odds ratio. pval: p-value effect. Note, statistics n_tot, , ci required. riskdiff (list) risk (proportion) difference column added, list settings apply within column. See tern::control_riskdiff() details. NULL, risk difference column added. conf_level (numeric) value confidence level within range (0, 1). col_symbol_size (integer NULL) column index used determine relative size estimator plot symbol. Typically, symbol size proportional sample size used calculate estimator. NULL, symbol size used subgroups. rel_width_forest (proportion) proportion total width allocate forest plot. Relative width table 1 - rel_width_forest. as_list = TRUE, parameter ignored. font_size (numeric(1)) font size. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. module, argument accept ggplot2_args object labs list following child elements: title, caption. elements taken account. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_forest_rsp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Response Forest Plot — template_forest_rsp","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_forest_tte.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Survival Forest Plot — template_forest_tte","title":"Template: Survival Forest Plot — template_forest_tte","text":"Creates valid expression generate survival forest plot.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_forest_tte.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Survival Forest Plot — template_forest_tte","text":"","code":"template_forest_tte( dataname = \"ANL\", parentname = \"ANL_ADSL\", arm_var, ref_arm = NULL, comp_arm = NULL, obj_var_name = \"\", aval_var = \"AVAL\", cnsr_var = \"CNSR\", subgroup_var, strata_var = NULL, stats = c(\"n_tot_events\", \"n_events\", \"median\", \"hr\", \"ci\"), riskdiff = NULL, conf_level = 0.95, col_symbol_size = NULL, time_unit_var = \"AVALU\", rel_width_forest = 0.25, font_size = 15, ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_forest_tte.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Survival Forest Plot — template_forest_tte","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. obj_var_name (character) additional text append table title. aval_var (character) name analysis value variable. cnsr_var (character) name censoring variable. subgroup_var (character) variable names can used subgroups. strata_var (character) names variables stratified analysis. stats (character) names statistics reported among: n_tot_events: Total number events per group. n_events: Number events per group. n_tot: Total number observations per group. n: Number observations per group. median: Median survival time. hr: Hazard ratio. ci: Confidence interval hazard ratio. pval: p-value effect. Note, one statistics n_tot n_tot_events, well hr ci required. riskdiff (list) risk (proportion) difference column added, list settings apply within column. See tern::control_riskdiff() details. NULL, risk difference column added. conf_level (numeric) value confidence level within range (0, 1). col_symbol_size (integer NULL) column index used determine relative size estimator plot symbol. Typically, symbol size proportional sample size used calculate estimator. NULL, symbol size used subgroups. time_unit_var (character) name variable representing time units. rel_width_forest (proportion) proportion total width allocate forest plot. Relative width table 1 - rel_width_forest. as_list = TRUE, parameter ignored. font_size (numeric) font size value. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_forest_tte.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Survival Forest Plot — template_forest_tte","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_ci.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Confidence Interval Plot — template_g_ci","title":"Template: Confidence Interval Plot — template_g_ci","text":"Creates valid expression generate ggplot2::ggplot() confidence interval plot.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_ci.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Confidence Interval Plot — template_g_ci","text":"","code":"template_g_ci( dataname, x_var, y_var, grp_var = NULL, stat = c(\"mean\", \"median\"), conf_level = 0.95, unit_var = \"AVALU\", ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_ci.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Confidence Interval Plot — template_g_ci","text":"dataname (character) analysis data used teal module. x_var (character) name treatment variable put x-axis. y_var (character) name response variable put y-axis. grp_var (character) name group variable used determine plot colors, point shapes, line types. stat (character) statistic plot. Options \"mean\" \"median\". conf_level (numeric) value confidence level within range (0, 1). unit_var (character) name unit variable. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_ci.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Confidence Interval Plot — template_g_ci","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_ipp.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Individual Patient Plots — template_g_ipp","title":"Template: Individual Patient Plots — template_g_ipp","text":"Creates valid expression generate ggplot2::ggplot() plots individual patients.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_ipp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Individual Patient Plots — template_g_ipp","text":"","code":"template_g_ipp( dataname = \"ANL\", paramcd, arm_var, arm_levels, avalu_first, paramcd_first, aval_var = \"AVAL\", avalu_var = \"AVALU\", id_var = \"USUBJID\", visit_var = \"AVISIT\", base_var = lifecycle::deprecated(), baseline_var = \"BASE\", add_baseline_hline = FALSE, separate_by_obs = FALSE, ggplot2_args = teal.widgets::ggplot2_args(), suppress_legend = FALSE, add_avalu = TRUE )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_ipp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Individual Patient Plots — template_g_ipp","text":"dataname (character) analysis data used teal module. paramcd (character) name parameter code variable. arm_var (character) variable names can used arm_var. arm_levels (character) vector levels arm_var. avalu_first (character)avalu_var text append plot title y-axis label add_avalu TRUE. paramcd_first (character)paramcd text append plot title y-axis label. aval_var (character) name analysis value variable. avalu_var (character) name analysis value unit variable. id_var (character) variable name subject id. visit_var (character) name variable visit timepoints. base_var Please use baseline_var argument instead. baseline_var (character) name variable baseline values analysis variable. add_baseline_hline (logical) whether horizontal line added plot baseline y-value. separate_by_obs (logical) whether create multi-panel plots. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. module, argument accept ggplot2_args object labs list following child elements: title, subtitle, x, y. elements taken account. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). suppress_legend (logical) whether suppress plot legend. add_avalu (logical) whether avalu_first text appended plot title y-axis label.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_ipp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Individual Patient Plots — template_g_ipp","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_km.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Kaplan-Meier Plot — template_g_km","title":"Template: Kaplan-Meier Plot — template_g_km","text":"Creates valid expression generate Kaplan-Meier plot.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_km.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Kaplan-Meier Plot — template_g_km","text":"","code":"template_g_km( dataname = \"ANL\", arm_var = \"ARM\", ref_arm = NULL, comp_arm = NULL, compare_arm = FALSE, combine_comp_arms = FALSE, aval_var = \"AVAL\", cnsr_var = \"CNSR\", xticks = NULL, strata_var = NULL, time_points = NULL, facet_var = \"SEX\", font_size = 11, conf_level = 0.95, ties = \"efron\", xlab = \"Survival time\", time_unit_var = \"AVALU\", yval = \"Survival\", ylim = NULL, pval_method = \"log-rank\", annot_surv_med = TRUE, annot_coxph = TRUE, control_annot_surv_med = control_surv_med_annot(), control_annot_coxph = control_coxph_annot(x = 0.27, y = 0.35, w = 0.3), legend_pos = NULL, position_coxph = lifecycle::deprecated(), width_annots = lifecycle::deprecated(), rel_height_plot = 0.8, ci_ribbon = FALSE, title = \"KM Plot\" )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_km.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Kaplan-Meier Plot — template_g_km","text":"dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. compare_arm (logical) triggers comparison study arms. combine_comp_arms (logical) triggers combination comparison arms. aval_var (character) name analysis value variable. cnsr_var (character) name censoring variable. xticks (numeric NULL) numeric vector tick positions single number spacing ticks x-axis. NULL (default), labeling::extended() used determine optimal tick positions x-axis. strata_var (character) names variables stratified analysis. time_points (character) time points can used tern::surv_timepoint(). facet_var (character) name variable use facet plot. font_size (numeric) font size value. conf_level (numeric) value confidence level within range (0, 1). ties (string) among exact (equivalent DISCRETE SAS), efron breslow, see survival::coxph(). Note: equivalent SAS EXACT method R. xlab (string) x-axis label. time_unit_var (character) name variable representing time units. yval (string) type plot, plotted y-axis. Options Survival (default) Failure probability. ylim (numeric(2)) vector containing lower upper limits y-axis, respectively. NULL (default), default scale range used. pval_method (string) method used estimation p.values; wald (default) likelihood. annot_surv_med (flag) compute add annotation table Kaplan-Meier curve estimating median survival time per group. annot_coxph (flag) whether add annotation table survival::coxph() model. control_annot_surv_med (list) parameters control position size annotation table added plot annot_surv_med = TRUE, specified using control_surv_med_annot() function. Parameter options : x, y, w, h, fill. See control_surv_med_annot() details. control_annot_coxph (list) parameters control position size annotation table added plot annot_coxph = TRUE, specified using control_coxph_annot() function. Parameter options : x, y, w, h, fill, ref_lbls. See control_coxph_annot() details. legend_pos (numeric(2) NULL) vector containing x- y-coordinates, respectively, legend position relative KM plot area. NULL (default), legend positioned bottom right corner plot, middle right plot needed prevent overlapping. position_coxph Please use x y elements control_annot_coxph instead. width_annots Please use w element control_annot_surv_med (surv_med) control_annot_coxph (coxph).\" rel_height_plot (proportion) proportion total figure height allocate Kaplan-Meier plot. Relative height patients risk table 1 - rel_height_plot. annot_at_risk = FALSE as_list = TRUE, parameter ignored. ci_ribbon (flag) whether confidence interval drawn around Kaplan-Meier curve. title (character) title output.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_km.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Kaplan-Meier Plot — template_g_km","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_lineplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Line Plot — template_g_lineplot","title":"Template: Line Plot — template_g_lineplot","text":"Creates valid expression generate ggplot2::ggplot() line plot.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_lineplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Line Plot — template_g_lineplot","text":"","code":"template_g_lineplot( dataname = \"ANL\", strata = lifecycle::deprecated(), group_var = \"ARM\", x = \"AVISIT\", y = \"AVAL\", y_unit = \"AVALU\", paramcd = \"PARAMCD\", param = \"ALT\", mid = \"mean\", interval = \"mean_ci\", whiskers = c(\"mean_ci_lwr\", \"mean_ci_upr\"), table = c(\"n\", \"mean_sd\", \"median\", \"range\"), mid_type = \"pl\", conf_level = 0.95, incl_screen = TRUE, mid_point_size = 2, table_font_size = 4, title = \"Line Plot\", y_lab = \"\", ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_lineplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Line Plot — template_g_lineplot","text":"dataname (character) analysis data used teal module. strata Please use group_var argument instead. group_var (string NA) group variable name. x (string) x-variable name. y (string) y-variable name. y_unit (string NA) y-axis unit variable name. paramcd (string NA) parameter code variable name. param (character) parameter filter data . mid (character NULL) names statistics plotted midpoints. statistics indicated mid variable must present object returned sfun, double numeric type vector length one. interval (character NULL) names statistics plotted intervals. statistics indicated interval variable must present object returned sfun, double numeric type vector length two. Set interval = NULL intervals added plot. whiskers (character) names interval whiskers plotted. Names must match names list element interval returned sfun (e.g. mean_ci_lwr element sfun(x)[[\"mean_ci\"]]). possible specify one whisker , suppress whiskers setting interval = NULL. table (character NULL) names statistics displayed table plot. statistics indicated table variable must present object returned sfun. mid_type (string) controls type mid plot, can point (\"p\"), line (\"l\"), point line (\"pl\"). conf_level (numeric) value confidence level within range (0, 1). incl_screen (logical) whether screening visit included. mid_point_size (numeric(1)) font size mid plot points. table_font_size (numeric(1)) font size text table. title (string) plot title. y_lab (string NULL) y-axis label. NULL label added. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. module, argument accept ggplot2_args object labs list following child elements: title, subtitle, caption, y, lty. elements taken account. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_g_lineplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Line Plot — template_g_lineplot","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_laboratory.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Laboratory Table — template_laboratory","title":"Template: Patient Profile Laboratory Table — template_laboratory","text":"Creates valid expression generate patient profile laboratory table using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_laboratory.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Laboratory Table — template_laboratory","text":"","code":"template_laboratory( dataname = \"ANL\", paramcd = \"PARAMCD\", param = \"PARAM\", anrind = \"ANRIND\", timepoints = \"ADY\", aval = lifecycle::deprecated(), aval_var = \"AVAL\", avalu = lifecycle::deprecated(), avalu_var = \"AVALU\", patient_id = NULL, round_value = 0L )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_laboratory.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Laboratory Table — template_laboratory","text":"dataname (character) analysis data used teal module. paramcd (character) name parameter code variable. param (character) name parameter variable. anrind (character) name analysis reference range indicator variable. timepoints (character) name time variable. aval Please use aval_var argument instead. aval_var (character) name analysis value variable. avalu Please use avalu_var argument instead. avalu_var (character) name analysis value unit variable. patient_id (character) patient ID. round_value (numeric) number decimal places round .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_laboratory.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Laboratory Table — template_laboratory","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_logistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Logistic Regression — template_logistic","title":"Template: Logistic Regression — template_logistic","text":"Creates valid expression generate logistic regression table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_logistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Logistic Regression — template_logistic","text":"","code":"template_logistic( dataname, arm_var, aval_var, paramcd = lifecycle::deprecated(), label_paramcd, cov_var, interaction_var, ref_arm, comp_arm, topleft = \"Logistic Regression\", conf_level = 0.95, combine_comp_arms = FALSE, responder_val = c(\"CR\", \"PR\"), at = NULL, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_logistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Logistic Regression — template_logistic","text":"dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. fit logistic model arm/treatment variable, set NULL. aval_var (character) name analysis value variable. paramcd paramcd argument used function. label_paramcd (character) label response parameter value print table title. cov_var (character) names covariates variables. interaction_var (character) names variables can used interaction variable selection. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. topleft (character) text use top-left annotation table. conf_level (numeric) value confidence level within range (0, 1). combine_comp_arms (logical) triggers combination comparison arms. responder_val (character) values responder variable corresponding successful response. (numeric NULL) optional values interaction variable. Otherwise median used. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_logistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Logistic Regression — template_logistic","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_medical_history.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Medical History — template_medical_history","title":"Template: Patient Profile Medical History — template_medical_history","text":"Creates valid expression generate patient profile medical history report using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_medical_history.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Medical History — template_medical_history","text":"","code":"template_medical_history( dataname = \"ANL\", mhterm = \"MHTERM\", mhbodsys = \"MHBODSYS\", mhdistat = \"MHDISTAT\", patient_id = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_medical_history.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Medical History — template_medical_history","text":"dataname (character) analysis data used teal module. mhterm (character) name reported term medical history variable. mhbodsys (character) name body system organ class variable. mhdistat (character) name status disease variable. patient_id (character) patient ID.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_medical_history.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Medical History — template_medical_history","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_mult_events.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Multiple Events by Term — template_mult_events","title":"Template: Multiple Events by Term — template_mult_events","text":"Creates valid expression generate table multiple events term.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_mult_events.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Multiple Events by Term — template_mult_events","text":"","code":"template_mult_events( dataname, parentname, arm_var, seq_var, hlt, llt, add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), event_type = \"event\", drop_arm_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_mult_events.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Multiple Events by Term — template_mult_events","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. seq_var (character) name analysis sequence number variable. Used counting unique number events. hlt (character) name variable high level term events. llt (character) name variable low level term events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). event_type (character) type event summarized (e.g. adverse event, treatment). Default \"event\". drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_mult_events.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Multiple Events by Term — template_mult_events","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_patient_timeline.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Timeline Plot — template_patient_timeline","title":"Template: Patient Profile Timeline Plot — template_patient_timeline","text":"Creates valid expression generate patient profile timeline ggplot2::ggplot() plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_patient_timeline.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Timeline Plot — template_patient_timeline","text":"","code":"template_patient_timeline( dataname = \"ANL\", aeterm = \"AETERM\", aetime_start = \"ASTDTM\", aetime_end = \"AENDTM\", dstime_start = \"CMASTDTM\", dstime_end = \"CMAENDTM\", cmdecod = \"CMDECOD\", aerelday_start = NULL, aerelday_end = NULL, dsrelday_start = NULL, dsrelday_end = NULL, relative_day = FALSE, patient_id, font_size = 12L, ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_patient_timeline.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Timeline Plot — template_patient_timeline","text":"dataname (character) analysis data used teal module. aeterm (character) name reported term adverse event variable. aetime_start (character) name start date/time adverse event variable. aetime_end (character) name end date/time adverse event variable. dstime_start (character) name date/time first exposure treatment variable. dstime_end (character) name date/time last exposure treatment variable. cmdecod (character) name standardized medication name variable. aerelday_start (character) name adverse event study start day variable. aerelday_end (character) name adverse event study end day variable. dsrelday_start (character) name concomitant medications study start day variable. dsrelday_end (character) name concomitant medications study day start variable. relative_day (logical) whether use relative days (TRUE) absolute dates (FALSE). patient_id (character) patient ID. font_size (numeric) font size value. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_patient_timeline.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Timeline Plot — template_patient_timeline","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_prior_medication.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Prior Medication — template_prior_medication","title":"Template: Patient Profile Prior Medication — template_prior_medication","text":"Creates valid expression generate patient profile prior medication report using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_prior_medication.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Prior Medication — template_prior_medication","text":"","code":"template_prior_medication( dataname = \"ANL\", atirel = \"ATIREL\", cmdecod = \"CMDECOD\", cmindc = \"CMINDC\", cmstdy = \"CMSTDY\" )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_prior_medication.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Prior Medication — template_prior_medication","text":"dataname (character) analysis data used teal module. atirel (character) name time relation medication variable. cmdecod (character) name standardized medication name variable. cmindc (character) name indication variable. cmstdy (character) name study relative day start medication variable.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_prior_medication.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Prior Medication — template_prior_medication","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_shift_by_arm.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Shift by Arm — template_shift_by_arm","title":"Template: Shift by Arm — template_shift_by_arm","text":"Creates valid expression generate summary table analysis indicator levels arm.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_shift_by_arm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Shift by Arm — template_shift_by_arm","text":"","code":"template_shift_by_arm( dataname, parentname, arm_var = \"ARM\", paramcd = \"PARAMCD\", visit_var = \"AVISIT\", treatment_flag_var = \"ONTRTFL\", treatment_flag = \"Y\", aval_var = \"ANRIND\", base_var = lifecycle::deprecated(), baseline_var = \"BNRIND\", na.rm = FALSE, na_level = default_na_str(), add_total = FALSE, total_label = default_total_label(), basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_shift_by_arm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Shift by Arm — template_shift_by_arm","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. paramcd (character) name parameter code variable. visit_var (character) variable names can used visit variable. Must factor dataname. treatment_flag_var (character) name treatment flag variable. treatment_flag (character) name value indicating treatment records treatment_flag_var. aval_var (character) name analysis reference range indicator variable. base_var Please use baseline_var argument instead. baseline_var (character) name baseline reference range indicator variable. na.rm (logical) whether NA values removed prior analysis. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). add_total (logical) whether include row total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_shift_by_arm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Shift by Arm — template_shift_by_arm","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_shift_by_arm_by_worst.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Shift by Arm by Worst Analysis Indicator Level — template_shift_by_arm_by_worst","title":"Template: Shift by Arm by Worst Analysis Indicator Level — template_shift_by_arm_by_worst","text":"Creates valid expression generate summary table worst analysis indicator variable level per subject arm.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_shift_by_arm_by_worst.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Shift by Arm by Worst Analysis Indicator Level — template_shift_by_arm_by_worst","text":"","code":"template_shift_by_arm_by_worst( dataname, parentname, arm_var = \"ARM\", paramcd = \"PARAMCD\", worst_flag_var = \"WORS02FL\", worst_flag = \"Y\", treatment_flag_var = \"ONTRTFL\", treatment_flag = \"Y\", aval_var = \"ANRIND\", base_var = lifecycle::deprecated(), baseline_var = \"BNRIND\", na.rm = FALSE, na_level = default_na_str(), add_total = FALSE, total_label = default_total_label(), basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_shift_by_arm_by_worst.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Shift by Arm by Worst Analysis Indicator Level — template_shift_by_arm_by_worst","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. paramcd (character) name parameter code variable. worst_flag_var (character) name worst flag variable. worst_flag (character) value indicating worst analysis indicator level. treatment_flag_var (character) name treatment flag variable. treatment_flag (character) name value indicating treatment records treatment_flag_var. aval_var (character) name analysis reference range indicator variable. base_var Please use baseline_var argument instead. baseline_var (character) name baseline reference range indicator variable. na.rm (logical) whether NA values removed prior analysis. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). add_total (logical) whether include row total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_shift_by_arm_by_worst.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Shift by Arm by Worst Analysis Indicator Level — template_shift_by_arm_by_worst","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_shift_by_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Grade Summary Table — template_shift_by_grade","title":"Template: Grade Summary Table — template_shift_by_grade","text":"Creates valid expression generate grade summary table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_shift_by_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Grade Summary Table — template_shift_by_grade","text":"","code":"template_shift_by_grade( parentname, dataname, arm_var = \"ARM\", id_var = \"USUBJID\", visit_var = \"AVISIT\", worst_flag_var = c(\"WGRLOVFL\", \"WGRLOFL\", \"WGRHIVFL\", \"WGRHIFL\"), worst_flag_indicator = \"Y\", anl_toxgrade_var = \"ATOXGR\", base_toxgrade_var = \"BTOXGR\", paramcd = \"PARAMCD\", drop_arm_levels = TRUE, add_total = FALSE, total_label = default_total_label(), na_level = default_na_str(), code_missing_baseline = FALSE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_shift_by_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Grade Summary Table — template_shift_by_grade","text":"parentname (character) parent analysis data used teal module, usually refers ADSL. dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. id_var (character) variable name subject id. visit_var (character) variable names can used visit variable. Must factor dataname. worst_flag_var (character) name worst flag variable. worst_flag_indicator (character) value indicating worst grade. anl_toxgrade_var (character) name variable indicating analysis toxicity grade. base_toxgrade_var (character) name variable indicating baseline toxicity grade. paramcd (character) name parameter code variable. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). code_missing_baseline (logical) whether missing baseline grades counted grade 0. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_shift_by_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Grade Summary Table — template_shift_by_grade","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_smq.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Adverse Events Table by Standardized MedDRA Query — template_smq","title":"Template: Adverse Events Table by Standardized MedDRA Query — template_smq","text":"Creates valid expression generate adverse events table Standardized MedDRA Query.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_smq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Adverse Events Table by Standardized MedDRA Query — template_smq","text":"","code":"template_smq( dataname, parentname, arm_var, llt = \"AEDECOD\", add_total = TRUE, total_label = default_total_label(), sort_criteria = c(\"freq_desc\", \"alpha\"), drop_arm_levels = TRUE, na_level = default_na_str(), smq_varlabel = \"Standardized MedDRA Query\", baskets = c(\"SMQ01NAM\", \"SMQ02NAM\", \"CQ01NAM\"), id_var = \"USUBJID\", basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_smq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Adverse Events Table by Standardized MedDRA Query — template_smq","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. llt (character) name variable low level term events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). sort_criteria (character) sort final table. Default option freq_desc sorts column sort_freq_col decreasing number patients event. Alternative option alpha sorts events alphabetically. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). smq_varlabel (character) label use new column SMQ created tern::h_stack_by_baskets(). baskets (character) names selected standardized/customized queries variables. id_var (character) variable name subject id. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_smq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Adverse Events Table by Standardized MedDRA Query — template_smq","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_summary.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Summary of Variables — template_summary","title":"Template: Summary of Variables — template_summary","text":"Creates valid expression generate table summarize variables.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_summary.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Summary of Variables — template_summary","text":"","code":"template_summary( dataname, parentname, arm_var, sum_vars, show_labels = lifecycle::deprecated(), add_total = TRUE, total_label = default_total_label(), var_labels = character(), arm_var_labels = NULL, na.rm = FALSE, na_level = default_na_str(), numeric_stats = c(\"n\", \"mean_sd\", \"mean_ci\", \"median\", \"median_ci\", \"quantiles\", \"range\", \"geom_mean\"), denominator = c(\"N\", \"n\", \"omit\"), drop_arm_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_summary.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Summary of Variables — template_summary","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. sum_vars (character) names variables summarized. show_labels add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). var_labels (named character) optional variable labels relabeling analysis variables. arm_var_labels (character NULL) vector column variable labels display, length arm_var. NULL, labels displayed. na.rm (logical) whether NA values removed prior analysis. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). numeric_stats (character) names statistics display numeric summary variables. Available statistics n, mean_sd, mean_ci, median, median_ci, quantiles, range, geom_mean. denominator (character) chooses percentages calculated. option N, reference population column total used denominator. option n, number non-missing records row column intersection used denominator. omit chosen, percentage omitted. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_summary.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Summary of Variables — template_summary","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_summary_by.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Summarize Variables by Row Groups Module — template_summary_by","title":"Template: Summarize Variables by Row Groups Module — template_summary_by","text":"Creates valid expression generate table summarize variables row groups.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_summary_by.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Summarize Variables by Row Groups Module — template_summary_by","text":"","code":"template_summary_by( parentname, dataname, arm_var, id_var, sum_vars, by_vars, var_labels = character(), add_total = TRUE, total_label = default_total_label(), parallel_vars = FALSE, row_groups = FALSE, na.rm = FALSE, na_level = default_na_str(), numeric_stats = c(\"n\", \"mean_sd\", \"mean_ci\", \"median\", \"median_ci\", \"quantiles\", \"range\"), denominator = c(\"N\", \"n\", \"omit\"), drop_arm_levels = TRUE, drop_zero_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_summary_by.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Summarize Variables by Row Groups Module — template_summary_by","text":"parentname (character) parent analysis data used teal module, usually refers ADSL. dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. id_var (character) variable name subject id. sum_vars (character) names variables summarized. by_vars (character) variable names used split summary rows. var_labels (named character) optional variable labels relabeling analysis variables. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). parallel_vars (logical) whether summarized variables arranged columns. Can set TRUE chosen analysis variables numeric. row_groups (logical) whether summarized variables arranged row groups. na.rm (logical) whether NA values removed prior analysis. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). numeric_stats (character) names statistics display numeric summary variables. Available statistics n, mean_sd, mean_ci, median, median_ci, quantiles, range, geom_mean. denominator (character) chooses percentages calculated. option N, reference population column total used denominator. option n, number non-missing records row column intersection used denominator. omit chosen, percentage omitted. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. drop_zero_levels (logical) whether rows zero counts columns removed table. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_summary_by.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Summarize Variables by Row Groups Module — template_summary_by","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_therapy.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Therapy Table and Plot — template_therapy","title":"Template: Patient Profile Therapy Table and Plot — template_therapy","text":"Creates valid expression generate patient profile therapy table ggplot2::ggplot() plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_therapy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Therapy Table and Plot — template_therapy","text":"","code":"template_therapy( dataname = \"ANL\", atirel = \"ATIREL\", cmdecod = \"CMDECOD\", cmindc = \"CMINDC\", cmdose = \"CMDOSE\", cmtrt = \"CMTRT\", cmdosu = \"CMDOSU\", cmroute = \"CMROUTE\", cmdosfrq = \"CMDOSFRQ\", cmstdy = \"CMSTDY\", cmendy = \"CMENDY\", patient_id, font_size = 12L, ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_therapy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Therapy Table and Plot — template_therapy","text":"dataname (character) analysis data used teal module. atirel (character) name time relation medication variable. cmdecod (character) name standardized medication name variable. cmindc (character) name indication variable. cmdose (character) name dose per administration variable. cmtrt (character) name reported name drug, med, therapy variable. cmdosu (character) name dose units variable. cmroute (character) name route administration variable. cmdosfrq (character) name dosing frequency per interval variable. cmstdy (character) name study relative day start medication variable. cmendy (character) name study day end medication variable. patient_id (character) patient ID. font_size (numeric) font size value. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_therapy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Therapy Table and Plot — template_therapy","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_tte.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Time-To-Event — template_tte","title":"Template: Time-To-Event — template_tte","text":"Creates valid expression generate time--event analysis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_tte.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Time-To-Event — template_tte","text":"","code":"template_tte( dataname = \"ANL\", parentname = \"ADSL\", arm_var = \"ARM\", paramcd, ref_arm = NULL, comp_arm = NULL, compare_arm = FALSE, combine_comp_arms = FALSE, aval_var = \"AVAL\", cnsr_var = \"CNSR\", strata_var = NULL, time_points = NULL, time_unit_var = \"AVALU\", event_desc_var = \"EVNTDESC\", control = control_tte(), add_total = FALSE, total_label = default_total_label(), na_level = default_na_str(), basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_tte.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Time-To-Event — template_tte","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. paramcd (character) endpoint parameter value use table title. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. compare_arm (logical) triggers comparison study arms. combine_comp_arms (logical) triggers combination comparison arms. aval_var (character) name analysis value variable. cnsr_var (character) name censoring variable. strata_var (character) names variables stratified analysis. time_points (character) time points can used tern::surv_timepoint(). time_unit_var (character) name variable representing time units. event_desc_var (character) name variable events description. control (list) list settings analysis. See control_tte() details. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_tte.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Time-To-Event — template_tte","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_vitals.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Vitals Plot — template_vitals","title":"Template: Patient Profile Vitals Plot — template_vitals","text":"Creates valid expression generate patient profile vitals ggplot2::ggplot() plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_vitals.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Vitals Plot — template_vitals","text":"","code":"template_vitals( dataname = \"ANL\", paramcd = \"PARAMCD\", paramcd_levels = c(\"SYSBP\", \"DIABP\", \"PUL\", \"RESP\", \"OXYSAT\", \"WGHT\", \"TEMP\"), xaxis = \"ADY\", aval = lifecycle::deprecated(), aval_var = \"AVAL\", patient_id, font_size = 12L, ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_vitals.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Vitals Plot — template_vitals","text":"dataname (character) analysis data used teal module. paramcd (character) name parameter code variable. paramcd_levels (character) vector levels paramcd. xaxis (character) name time variable put x-axis. aval Please use aval_var argument instead. aval_var (character) name analysis value variable. patient_id (character) patient ID. font_size (numeric) font size value. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/template_vitals.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Vitals Plot — template_vitals","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_gee.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"module produces analysis table using Generalized Estimating Equations (GEE).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_gee.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"","code":"tm_a_gee( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), aval_var, id_var, arm_var, visit_var, cov_var, arm_ref_comp = NULL, paramcd, conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_gee.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. id_var (teal.transform::choices_selected()) object specifying variable name subject id. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. visit_var (teal.transform::choices_selected()) object available choices preselected option variable names can used visit variable. Must factor dataname. cov_var (teal.transform::choices_selected()) object available choices preselected option covariates variables. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_gee.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_gee.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"module generates following objects, can modified place using decorators: table (ElementaryTable - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_gee.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_gee.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"","code":"library(dplyr) #> #> Attaching package: ‘dplyr’ #> The following object is masked from ‘package:testthat’: #> #> matches #> The following objects are masked from ‘package:stats’: #> #> filter, lag #> The following objects are masked from ‘package:base’: #> #> intersect, setdiff, setequal, union data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADQS <- tmc_ex_adqs %>% filter(ABLFL != \"Y\" & ABLFL2 != \"Y\") %>% mutate( AVISIT = as.factor(AVISIT), AVISITN = rank(AVISITN) %>% as.factor() %>% as.numeric() %>% as.factor(), AVALBIN = AVAL < 50 # Just as an example to get a binary endpoint. ) %>% droplevels() }) join_keys(data) <- default_cdisc_join_keys[names(data)] app <- init( data = data, modules = modules( tm_a_gee( label = \"GEE\", dataname = \"ADQS\", aval_var = choices_selected(\"AVALBIN\", fixed = TRUE), id_var = choices_selected(c(\"USUBJID\", \"SUBJID\"), \"USUBJID\"), arm_var = choices_selected(c(\"ARM\", \"ARMCD\"), \"ARM\"), visit_var = choices_selected(c(\"AVISIT\", \"AVISITN\"), \"AVISIT\"), paramcd = choices_selected( choices = value_choices(data[[\"ADQS\"]], \"PARAMCD\", \"PARAM\"), selected = \"FKSI-FWB\" ), cov_var = choices_selected(c(\"BASE\", \"AGE\", \"SEX\", \"BASE:AVISIT\"), NULL) ) ) ) #> Initializing tm_a_gee (prototype) #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_mmrm.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"module produces analysis tables plots Mixed Model Repeated Measurements.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_mmrm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"","code":"tm_a_mmrm( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), aval_var, id_var, arm_var, visit_var, cov_var, arm_ref_comp = NULL, paramcd, method = teal.transform::choices_selected(c(\"Satterthwaite\", \"Kenward-Roger\", \"Kenward-Roger-Linear\"), \"Satterthwaite\", keep_order = TRUE), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), plot_height = c(700L, 200L, 2000L), plot_width = NULL, total_label = default_total_label(), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_mmrm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. id_var (teal.transform::choices_selected()) object specifying variable name subject id. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. visit_var (teal.transform::choices_selected()) object available choices preselected option variable names can used visit variable. Must factor dataname. cov_var (teal.transform::choices_selected()) object available choices preselected option covariates variables. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. method (teal.transform::choices_selected()) object available choices pre-selected option adjustment method. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings plots named list ggplot2_args objects plot-specific settings. List names match following: c(\"default\", \"lsmeans\", \"diagnostic\"). argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see help vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_mmrm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_mmrm.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"ordering input data sets can lead slightly different numerical results different convergence behavior. known observation used package lme4. However, convergence achieved, results reliable numerical precision.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_mmrm.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"module generates following objects, can modified place using decorators: lsmeans_plot (ggplot2) diagnostic_plot (TableTree- output rtables::build_table) lsmeans_table (TableTree- output rtables::build_table) covariance_table (TableTree- output rtables::build_table) fixed_effects_table (TableTree- output rtables::build_table) diagnostic_table (TableTree- output rtables::build_table) Decorators can applied outputs specific objects using named list teal_transform_module objects. \"default\" name reserved decorators applied outputs. See code snippet :","code":"tm_a_mrmm( ..., # arguments for module decorators = list( default = list(teal_transform_module(...)), # applied to all outputs lsmeans_plot = list(teal_transform_module(...)) # applied only to `lsmeans_plot` output diagnostic_plot = list(teal_transform_module(...)) # applied only to `diagnostic_plot` output lsmeans_table = list(teal_transform_module(...)) # applied only to `lsmeans_table` output covariance_table = list(teal_transform_module(...)) # applied only to `covariance_table` output fixed_effects_table = list(teal_transform_module(...)) # applied only to `fixed_effects_table` output diagnostic_table = list(teal_transform_module(...)) # applied only to `diagnostic_table` output ) )"},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_mmrm.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_a_mmrm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"","code":"library(dplyr) arm_ref_comp <- list( ARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ) ) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADQS <- tmc_ex_adqs %>% filter(ABLFL != \"Y\" & ABLFL2 != \"Y\") %>% filter(AVISIT %in% c(\"WEEK 1 DAY 8\", \"WEEK 2 DAY 15\", \"WEEK 3 DAY 22\")) %>% mutate( AVISIT = as.factor(AVISIT), AVISITN = rank(AVISITN) %>% as.factor() %>% as.numeric() %>% as.factor() #' making consecutive numeric factor ) }) join_keys(data) <- default_cdisc_join_keys[names(data)] app <- init( data = data, modules = modules( tm_a_mmrm( label = \"MMRM\", dataname = \"ADQS\", aval_var = choices_selected(c(\"AVAL\", \"CHG\"), \"AVAL\"), id_var = choices_selected(c(\"USUBJID\", \"SUBJID\"), \"USUBJID\"), arm_var = choices_selected(c(\"ARM\", \"ARMCD\"), \"ARM\"), visit_var = choices_selected(c(\"AVISIT\", \"AVISITN\"), \"AVISIT\"), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( choices = value_choices(data[[\"ADQS\"]], \"PARAMCD\", \"PARAM\"), selected = \"FKSI-FWB\" ), cov_var = choices_selected(c(\"BASE\", \"AGE\", \"SEX\", \"BASE:AVISIT\"), NULL) ) ) ) #> Initializing tm_a_mmrm #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_barchart_simple.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"module produces ggplot2::ggplot() type bar chart summary table counts per category.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_barchart_simple.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"","code":"tm_g_barchart_simple( x = NULL, fill = NULL, x_facet = NULL, y_facet = NULL, label = \"Count Barchart\", plot_options = NULL, plot_height = c(600L, 200L, 2000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_barchart_simple.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"x (data_extract_spec) variable x-axis. fill (data_extract_spec) grouping variable determine bar colors. x_facet (data_extract_spec) row-wise faceting groups. y_facet (data_extract_spec) column-wise faceting groups. label (character) menu item label module teal app. plot_options (list) list plot options. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_barchart_simple.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_barchart_simple.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"Categories can defined four levels deep defined x, fill, x_facet, y_facet parameters. parameters set NULL (default) ignored.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_barchart_simple.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_barchart_simple.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_barchart_simple.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl %>% mutate(ITTFL = factor(\"Y\") %>% with_label(\"Intent-To-Treat Population Flag\")) ADAE <- tmc_ex_adae %>% filter(!((AETOXGR == 1) & (AESEV == \"MILD\") & (ARM == \"A: Drug X\"))) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADAE <- data[[\"ADAE\"]] app <- init( data = data, modules = modules( tm_g_barchart_simple( label = \"ADAE Analysis\", x = data_extract_spec( dataname = \"ADSL\", select = select_spec( choices = variable_choices( ADSL, c( \"ARM\", \"ACTARM\", \"SEX\", \"RACE\", \"ITTFL\", \"SAFFL\", \"STRATA2\" ) ), selected = \"ACTARM\", multiple = FALSE ) ), fill = list( data_extract_spec( dataname = \"ADSL\", select = select_spec( choices = variable_choices( ADSL, c( \"ARM\", \"ACTARM\", \"SEX\", \"RACE\", \"ITTFL\", \"SAFFL\", \"STRATA2\" ) ), selected = \"SEX\", multiple = FALSE ) ), data_extract_spec( dataname = \"ADAE\", select = select_spec( choices = variable_choices(ADAE, c(\"AETOXGR\", \"AESEV\", \"AESER\")), selected = NULL, multiple = FALSE ) ) ), x_facet = list( data_extract_spec( dataname = \"ADAE\", select = select_spec( choices = variable_choices(ADAE, c(\"AETOXGR\", \"AESEV\", \"AESER\")), selected = \"AETOXGR\", multiple = FALSE ) ), data_extract_spec( dataname = \"ADSL\", select = select_spec( choices = variable_choices( ADSL, c( \"ARM\", \"ACTARM\", \"SEX\", \"RACE\", \"ITTFL\", \"SAFFL\", \"STRATA2\" ) ), selected = NULL, multiple = FALSE ) ) ), y_facet = list( data_extract_spec( dataname = \"ADAE\", select = select_spec( choices = variable_choices(ADAE, c(\"AETOXGR\", \"AESEV\", \"AESER\")), selected = \"AESEV\", multiple = FALSE ) ), data_extract_spec( dataname = \"ADSL\", select = select_spec( choices = variable_choices( ADSL, c( \"ARM\", \"ACTARM\", \"SEX\", \"RACE\", \"ITTFL\", \"SAFFL\", \"STRATA2\" ) ), selected = NULL, multiple = FALSE ) ) ) ) ) ) #> Initializing tm_g_barchart_simple #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ci.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Confidence Interval Plot — tm_g_ci","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"module produces ggplot2::ggplot() type confidence interval plot consistent TLG Catalog template CIG01 available .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ci.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"","code":"tm_g_ci( label, x_var, y_var, color, stat = c(\"mean\", \"median\"), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), plot_height = c(700L, 200L, 2000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ci.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"label (character) menu item label module teal app. x_var (character) name treatment variable put x-axis. y_var (character) name response variable put y-axis. color (data_extract_spec) group variable used determine plot colors, shapes, line types. stat (character) statistic plot. Options \"mean\" \"median\". conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ci.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ci.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ci.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ci.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"","code":"library(nestcolor) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_g_ci( label = \"Confidence Interval Plot\", x_var = data_extract_spec( dataname = \"ADSL\", select = select_spec( choices = c(\"ARMCD\", \"BMRKR2\"), selected = c(\"ARMCD\"), multiple = FALSE, fixed = FALSE ) ), y_var = data_extract_spec( dataname = \"ADLB\", filter = list( filter_spec( vars = \"PARAMCD\", choices = levels(ADLB$PARAMCD), selected = levels(ADLB$PARAMCD)[1], multiple = FALSE, label = \"Select lab:\" ), filter_spec( vars = \"AVISIT\", choices = levels(ADLB$AVISIT), selected = levels(ADLB$AVISIT)[1], multiple = FALSE, label = \"Select visit:\" ) ), select = select_spec( label = \"Analyzed Value\", choices = c(\"AVAL\", \"CHG\"), selected = \"AVAL\", multiple = FALSE, fixed = FALSE ) ), color = data_extract_spec( dataname = \"ADSL\", select = select_spec( label = \"Color by variable\", choices = c(\"SEX\", \"STRATA1\", \"STRATA2\"), selected = c(\"STRATA1\"), multiple = FALSE, fixed = FALSE ) ) ) ) ) #> Initializing tm_g_ci #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_rsp.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Forest Response Plot — tm_g_forest_rsp","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"module produces grid-style forest plot response data ADaM structure.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_rsp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"","code":"tm_g_forest_rsp( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, arm_ref_comp = NULL, paramcd, aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALC\"), \"AVALC\", fixed = TRUE), subgroup_var, strata_var, stats = c(\"n_tot\", \"n\", \"n_rsp\", \"prop\", \"or\", \"ci\"), riskdiff = NULL, fixed_symbol_size = TRUE, conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), default_responses = c(\"CR\", \"PR\", \"Y\", \"Complete Response (CR)\", \"Partial Response (PR)\"), plot_height = c(500L, 200L, 2000L), plot_width = c(1500L, 800L, 3000L), rel_width_forest = c(25L, 0L, 100L), font_size = c(15L, 1L, 30L), pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_rsp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. subgroup_var (teal.transform::choices_selected()) object available choices preselected option variable names can used default subgroups. strata_var (teal.transform::choices_selected()) names variables stratified analysis. stats (character) names statistics reported among: n: Total number observations per group. n_rsp: Number responders per group. prop: Proportion responders. n_tot: Total number observations. : Odds ratio. ci : Confidence interval odds ratio. pval: p-value effect. Note, statistics n_tot, , ci required. riskdiff (list) risk (proportion) difference column added, list settings apply within column. See tern::control_riskdiff() details. NULL, risk difference column added. fixed_symbol_size (logical) (TRUE), symbol size used plotting estimate. Otherwise, symbol size proportional sample size subgroup. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). default_responses (list character) defines default codes response variable module per value paramcd. passed vector transmitted paramcd values. passed list must named contain arrays, name corresponding single value paramcd. array may contain default response values named arrays rsp default selected response values levels default level choices. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. rel_width_forest (proportion) proportion total width allocate forest plot. Relative width table 1 - rel_width_forest. as_list = TRUE, parameter ignored. font_size (numeric(1)) font size. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. module, argument accept ggplot2_args object labs list following child elements: title, caption. elements taken account. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_rsp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_rsp.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_rsp.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_rsp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADRS <- tmc_ex_adrs %>% mutate(AVALC = d_onco_rsp_label(AVALC) %>% with_label(\"Character Result/Finding\")) %>% filter(PARAMCD != \"OVRINV\" | AVISIT == \"FOLLOW UP\") }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADRS <- data[[\"ADRS\"]] arm_ref_comp <- list( ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ), ARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ) ) app <- init( data = data, modules = modules( tm_g_forest_rsp( label = \"Forest Response\", dataname = \"ADRS\", arm_var = choices_selected( variable_choices(ADSL, c(\"ARM\", \"ARMCD\")), \"ARMCD\" ), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( value_choices(ADRS, \"PARAMCD\", \"PARAM\"), \"INVET\" ), subgroup_var = choices_selected( variable_choices(ADSL, names(ADSL)), c(\"BMRKR2\", \"SEX\") ), strata_var = choices_selected( variable_choices(ADSL, c(\"STRATA1\", \"STRATA2\")), \"STRATA2\" ), plot_height = c(600L, 200L, 2000L), default_responses = list( BESRSPI = list( rsp = c(\"Stable Disease (SD)\", \"Not Evaluable (NE)\"), levels = c( \"Complete Response (CR)\", \"Partial Response (PR)\", \"Stable Disease (SD)\", \"Progressive Disease (PD)\", \"Not Evaluable (NE)\" ) ), INVET = list( rsp = c(\"Complete Response (CR)\", \"Partial Response (PR)\"), levels = c( \"Complete Response (CR)\", \"Not Evaluable (NE)\", \"Partial Response (PR)\", \"Progressive Disease (PD)\", \"Stable Disease (SD)\" ) ), OVRINV = list( rsp = c(\"Progressive Disease (PD)\", \"Stable Disease (SD)\"), levels = c(\"Progressive Disease (PD)\", \"Stable Disease (SD)\", \"Not Evaluable (NE)\") ) ) ) ) ) #> Initializing tm_g_forest_rsp #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_tte.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Forest Survival Plot — tm_g_forest_tte","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"module produces grid-style forest plot time--event data ADaM structure.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_tte.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"","code":"tm_g_forest_tte( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, arm_ref_comp = NULL, subgroup_var, paramcd, strata_var, aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVAL\"), \"AVAL\", fixed = TRUE), cnsr_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"CNSR\"), \"CNSR\", fixed = TRUE), stats = c(\"n_tot_events\", \"n_events\", \"median\", \"hr\", \"ci\"), riskdiff = NULL, conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), time_unit_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALU\"), \"AVALU\", fixed = TRUE), fixed_symbol_size = TRUE, plot_height = c(500L, 200L, 2000L), plot_width = c(1500L, 800L, 3000L), rel_width_forest = c(25L, 0L, 100L), font_size = c(15L, 1L, 30L), pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_tte.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. subgroup_var (teal.transform::choices_selected()) object available choices preselected option variable names can used default subgroups. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. strata_var (teal.transform::choices_selected()) names variables stratified analysis. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. cnsr_var (teal.transform::choices_selected()) object available choices preselected option censoring variable. stats (character) names statistics reported among: n_tot_events: Total number events per group. n_events: Number events per group. n_tot: Total number observations per group. n: Number observations per group. median: Median survival time. hr: Hazard ratio. ci: Confidence interval hazard ratio. pval: p-value effect. Note, one statistics n_tot n_tot_events, well hr ci required. riskdiff (list) risk (proportion) difference column added, list settings apply within column. See tern::control_riskdiff() details. NULL, risk difference column added. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). time_unit_var (teal.transform::choices_selected()) object available choices pre-selected option time unit variable. fixed_symbol_size (logical) (TRUE), symbol size used plotting estimate. Otherwise, symbol size proportional sample size subgroup. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. rel_width_forest (proportion) proportion total width allocate forest plot. Relative width table 1 - rel_width_forest. as_list = TRUE, parameter ignored. font_size (numeric(1)) font size. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_tte.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_tte.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_tte.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_forest_tte.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADTTE <- tmc_ex_adtte ADSL$RACE <- droplevels(ADSL$RACE) %>% with_label(\"Race\") }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADTTE <- data[[\"ADTTE\"]] arm_ref_comp <- list( ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ), ARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ) ) app <- init( data = data, modules = modules( tm_g_forest_tte( label = \"Forest Survival\", dataname = \"ADTTE\", arm_var = choices_selected( variable_choices(ADSL, c(\"ARM\", \"ARMCD\")), \"ARMCD\" ), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( value_choices(ADTTE, \"PARAMCD\", \"PARAM\"), \"OS\" ), subgroup_var = choices_selected( variable_choices(ADSL, names(ADSL)), c(\"BMRKR2\", \"SEX\") ), strata_var = choices_selected( variable_choices(ADSL, c(\"STRATA1\", \"STRATA2\")), \"STRATA2\" ) ) ) ) #> Initializing tm_g_forest_tte #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ipp.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Individual Patient Plots — tm_g_ipp","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"module produces ggplot2::ggplot() type individual patient plots display trends parameter values time patient, using data ADaM structure.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ipp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"","code":"tm_g_ipp( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, paramcd, id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"USUBJID\"), \"USUBJID\", fixed = TRUE), visit_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVISIT\"), \"AVISIT\", fixed = TRUE), aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVAL\"), \"AVAL\", fixed = TRUE), avalu_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALU\"), \"AVALU\", fixed = TRUE), base_var = lifecycle::deprecated(), baseline_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"BASE\"), \"BASE\", fixed = TRUE), add_baseline_hline = FALSE, separate_by_obs = FALSE, suppress_legend = FALSE, add_avalu = TRUE, plot_height = c(1200L, 400L, 5000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ipp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable values can used arm variable. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. id_var (teal.transform::choices_selected()) object specifying variable name subject id. visit_var (teal.transform::choices_selected()) object available choices preselected option variable names can used visit variable. Must factor dataname. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. avalu_var (teal.transform::choices_selected()) object available choices preselected option analysis unit variable. base_var Please use baseline_var argument instead. baseline_var (teal.transform::choices_selected()) object available choices preselected option variable values can used baseline_var. add_baseline_hline (logical) whether horizontal line added plot baseline y-value. separate_by_obs (logical) whether create multi-panel plots. suppress_legend (logical) whether suppress plot legend. add_avalu (logical) whether avalu_first text appended plot title y-axis label. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. module, argument accept ggplot2_args object labs list following child elements: title, subtitle, x, y. elements taken account. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ipp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ipp.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ipp.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_ipp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl %>% slice(1:20) %>% df_explicit_na() ADLB <- tmc_ex_adlb %>% filter(USUBJID %in% ADSL$USUBJID) %>% df_explicit_na() %>% filter(AVISIT != \"SCREENING\") }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_g_ipp( label = \"Individual Patient Plot\", dataname = \"ADLB\", arm_var = choices_selected( value_choices(ADLB, \"ARMCD\"), \"ARM A\" ), paramcd = choices_selected( value_choices(ADLB, \"PARAMCD\"), \"ALT\" ), aval_var = choices_selected( variable_choices(ADLB, c(\"AVAL\", \"CHG\")), \"AVAL\" ), avalu_var = choices_selected( variable_choices(ADLB, c(\"AVALU\")), \"AVALU\", fixed = TRUE ), id_var = choices_selected( variable_choices(ADLB, c(\"USUBJID\")), \"USUBJID\", fixed = TRUE ), visit_var = choices_selected( variable_choices(ADLB, c(\"AVISIT\")), \"AVISIT\" ), baseline_var = choices_selected( variable_choices(ADLB, c(\"BASE\")), \"BASE\", fixed = TRUE ), add_baseline_hline = FALSE, separate_by_obs = FALSE ) ) ) #> Initializing tm_g_ipp #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_km.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Kaplan-Meier Plot — tm_g_km","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"module produces ggplot-style Kaplan-Meier plot data ADaM structure.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_km.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"","code":"tm_g_km( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, arm_ref_comp = NULL, paramcd, strata_var, facet_var, time_unit_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALU\"), \"AVALU\", fixed = TRUE), aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVAL\"), \"AVAL\", fixed = TRUE), cnsr_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"CNSR\"), \"CNSR\", fixed = TRUE), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), font_size = c(11L, 1L, 30), control_annot_surv_med = control_surv_med_annot(), control_annot_coxph = control_coxph_annot(x = 0.27, y = 0.35, w = 0.3), legend_pos = c(0.9, 0.5), rel_height_plot = c(80L, 0L, 100L), plot_height = c(800L, 400L, 5000L), plot_width = NULL, pre_output = NULL, post_output = NULL, decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_km.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. strata_var (teal.transform::choices_selected()) names variables stratified analysis. facet_var (teal.transform::choices_selected()) object available choices preselected option names variable can used plot faceting. time_unit_var (teal.transform::choices_selected()) object available choices pre-selected option time unit variable. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. cnsr_var (teal.transform::choices_selected()) object available choices preselected option censoring variable. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). font_size (numeric) numeric vector length 3 current, minimum maximum font size values. control_annot_surv_med (list) parameters control position size annotation table added plot annot_surv_med = TRUE, specified using control_surv_med_annot() function. Parameter options : x, y, w, h, fill. See control_surv_med_annot() details. control_annot_coxph (list) parameters control position size annotation table added plot annot_coxph = TRUE, specified using control_coxph_annot() function. Parameter options : x, y, w, h, fill, ref_lbls. See control_coxph_annot() details. legend_pos (numeric(2) NULL) vector containing x- y-coordinates, respectively, legend position relative KM plot area. NULL (default), legend positioned bottom right corner plot, middle right plot needed prevent overlapping. rel_height_plot (proportion) proportion total figure height allocate Kaplan-Meier plot. Relative height patients risk table 1 - rel_height_plot. annot_at_risk = FALSE as_list = TRUE, parameter ignored. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_km.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_km.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_km.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_km.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"","code":"library(nestcolor) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADTTE <- tmc_ex_adtte }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADTTE <- data[[\"ADTTE\"]] arm_ref_comp <- list( ACTARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ), ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ) ) app <- init( data = data, modules = modules( tm_g_km( label = \"Kaplan-Meier Plot\", dataname = \"ADTTE\", arm_var = choices_selected( variable_choices(ADSL, c(\"ARM\", \"ARMCD\", \"ACTARMCD\")), \"ARM\" ), paramcd = choices_selected( value_choices(ADTTE, \"PARAMCD\", \"PARAM\"), \"OS\" ), arm_ref_comp = arm_ref_comp, strata_var = choices_selected( variable_choices(ADSL, c(\"SEX\", \"BMRKR2\")), \"SEX\" ), facet_var = choices_selected( variable_choices(ADSL, c(\"SEX\", \"BMRKR2\")), NULL ) ) ) ) #> Initializing tm_g_km #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_lineplot.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Line Plot — tm_g_lineplot","title":"teal Module: Line Plot — tm_g_lineplot","text":"module produces ggplot2::ggplot() type line plot, optional summary table, standard ADaM data.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_lineplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Line Plot — tm_g_lineplot","text":"","code":"tm_g_lineplot( label, dataname, parentname = NULL, strata = lifecycle::deprecated(), group_var = teal.transform::choices_selected(teal.transform::variable_choices(parentname, c(\"ARM\", \"ARMCD\", \"ACTARMCD\")), \"ARM\"), x = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVISIT\"), \"AVISIT\", fixed = TRUE), y = teal.transform::choices_selected(teal.transform::variable_choices(dataname, c(\"AVAL\", \"BASE\", \"CHG\", \"PCHG\")), \"AVAL\"), y_unit = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALU\"), \"AVALU\", fixed = TRUE), paramcd = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"PARAMCD\"), \"PARAMCD\", fixed = TRUE), param = teal.transform::choices_selected(teal.transform::value_choices(dataname, \"PARAMCD\", \"PARAM\"), \"ALT\"), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), interval = \"mean_ci\", mid = \"mean\", whiskers = c(\"mean_ci_lwr\", \"mean_ci_upr\"), table = c(\"n\", \"mean_sd\", \"median\", \"range\"), mid_type = \"pl\", mid_point_size = c(2, 1, 5), table_font_size = c(4, 2, 6), plot_height = c(1000L, 200L, 4000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_lineplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Line Plot — tm_g_lineplot","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. strata Please use group_var argument instead. group_var (string NA) group variable name. x (string) x-variable name. y (string) y-variable name. y_unit (string NA) y-axis unit variable name. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. param (character) parameter filter data . conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). interval (character NULL) names statistics plotted intervals. statistics indicated interval variable must present object returned sfun, double numeric type vector length two. Set interval = NULL intervals added plot. mid (character NULL) names statistics plotted midpoints. statistics indicated mid variable must present object returned sfun, double numeric type vector length one. whiskers (character) names interval whiskers plotted. Names must match names list element interval returned sfun (e.g. mean_ci_lwr element sfun(x)[[\"mean_ci\"]]). possible specify one whisker , suppress whiskers setting interval = NULL. table (character NULL) names statistics displayed table plot. statistics indicated table variable must present object returned sfun. mid_type (string) controls type mid plot, can point (\"p\"), line (\"l\"), point line (\"pl\"). mid_point_size (numeric(1)) font size mid plot points. table_font_size (numeric(1)) font size text table. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. module, argument accept ggplot2_args object labs list following child elements: title, subtitle, caption, y, lty. elements taken account. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_lineplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Line Plot — tm_g_lineplot","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_lineplot.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Line Plot — tm_g_lineplot","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_lineplot.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Line Plot — tm_g_lineplot","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_lineplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Line Plot — tm_g_lineplot","text":"","code":"library(nestcolor) library(dplyr) library(forcats) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb %>% mutate(AVISIT == fct_reorder(AVISIT, AVISITN, min)) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_g_lineplot( label = \"Line Plot\", dataname = \"ADLB\", group_var = choices_selected( variable_choices(ADSL, c(\"ARM\", \"ARMCD\", \"ACTARMCD\")), \"ARM\" ), y = choices_selected( variable_choices(ADLB, c(\"AVAL\", \"BASE\", \"CHG\", \"PCHG\")), \"AVAL\" ), param = choices_selected( value_choices(ADLB, \"PARAMCD\", \"PARAM\"), \"ALT\" ) ) ) ) #> Initializing tm_g_lineplot #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_adverse_events.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"module produces adverse events table ggplot2::ggplot() type plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_adverse_events.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"","code":"tm_g_pp_adverse_events( label, dataname = \"ADAE\", parentname = \"ADSL\", patient_col = \"USUBJID\", aeterm = NULL, tox_grade = NULL, causality = NULL, outcome = NULL, action = NULL, time = NULL, decod = NULL, font_size = c(12L, 12L, 25L), plot_height = c(700L, 200L, 2000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_adverse_events.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. aeterm (teal.transform::choices_selected()) object available choices preselected option AETERM variable dataname. tox_grade (teal.transform::choices_selected()) object available choices preselected option AETOXGR variable dataname. causality (teal.transform::choices_selected()) object available choices preselected option AEREL variable dataname. outcome (teal.transform::choices_selected()) object available choices preselected option AEOUT variable dataname. action (teal.transform::choices_selected()) object available choices preselected option AEACN variable dataname. time (teal.transform::choices_selected()) object available choices preselected option ASTDY variable dataname. decod (teal.transform::choices_selected()) object available choices preselected option AEDECOD variable dataname. font_size (numeric) numeric vector length 3 current, minimum maximum font size values. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_adverse_events.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_adverse_events.html","id":"decorating-modules","dir":"Reference","previous_headings":"","what":"Decorating Modules","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"module generates following objects, can modified place using decorators:: plot (ggplot2) table (listing_df - output rlistings::as_listing) Decorators can applied outputs specific objects using named list teal_transform_module objects. \"default\" name reserved decorators applied outputs. See code snippet : additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":"tm_g_pp_adverse_events( ..., # arguments for module decorators = list( default = list(teal_transform_module(...)), # applied to all outputs plot = list(teal_transform_module(...)), # applied only to `plot` output table = list(teal_transform_module(...)) # applied only to `table` output ) )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_adverse_events.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_adverse_events.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADAE <- tmc_ex_adae ADSL <- tmc_ex_adsl %>% filter(USUBJID %in% ADAE$USUBJID) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADAE <- data[[\"ADAE\"]] app <- init( data = data, modules = modules( tm_g_pp_adverse_events( label = \"Adverse Events\", dataname = \"ADAE\", parentname = \"ADSL\", patient_col = \"USUBJID\", plot_height = c(600L, 200L, 2000L), aeterm = choices_selected( choices = variable_choices(ADAE, \"AETERM\"), selected = \"AETERM\" ), tox_grade = choices_selected( choices = variable_choices(ADAE, \"AETOXGR\"), selected = \"AETOXGR\" ), causality = choices_selected( choices = variable_choices(ADAE, \"AEREL\"), selected = \"AEREL\" ), outcome = choices_selected( choices = variable_choices(ADAE, \"AEOUT\"), selected = \"AEOUT\" ), action = choices_selected( choices = variable_choices(ADAE, \"AEACN\"), selected = \"AEACN\" ), time = choices_selected( choices = variable_choices(ADAE, \"ASTDY\"), selected = \"ASTDY\" ), decod = NULL ) ) ) #> Initializing tm_g_pp_adverse_events #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_patient_timeline.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"module produces patient profile timeline ggplot2::ggplot() type plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_patient_timeline.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"","code":"tm_g_pp_patient_timeline( label, dataname_adcm = \"ADCM\", dataname_adae = \"ADAE\", parentname = \"ADSL\", patient_col = \"USUBJID\", aeterm = NULL, cmdecod = NULL, aetime_start = NULL, aetime_end = NULL, dstime_start = NULL, dstime_end = NULL, aerelday_start = NULL, aerelday_end = NULL, dsrelday_start = NULL, dsrelday_end = NULL, font_size = c(12L, 12L, 25L), plot_height = c(700L, 200L, 2000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_patient_timeline.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"label (character) menu item label module teal app. dataname_adcm (character) name ADCM dataset equivalent. dataname_adae (character) name ADAE dataset equivalent. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. aeterm (teal.transform::choices_selected()) object available choices preselected option AETERM variable dataname. cmdecod (teal.transform::choices_selected()) object available choices preselected option CMDECOD variable dataname_adcm. aetime_start (teal.transform::choices_selected()) object available choices preselected option ASTDTM variable dataname_adae. aetime_end (teal.transform::choices_selected()) object available choices preselected option AENDTM variable dataname_adae. dstime_start (teal.transform::choices_selected()) object available choices preselected option CMASTDTM variable dataname_adcm. dstime_end (teal.transform::choices_selected()) object available choices preselected option CMAENDTM variable dataname_adcm. aerelday_start (teal.transform::choices_selected()) object available choices preselected option ASTDY variable dataname_adae. aerelday_end (teal.transform::choices_selected()) object available choices preselected option AENDY variable dataname_adae. dsrelday_start (teal.transform::choices_selected()) object available choices preselected option ASTDY variable dataname_adcm. dsrelday_end (teal.transform::choices_selected()) object available choices preselected option AENDY variable dataname_adcm. font_size (numeric) numeric vector length 3 current, minimum maximum font size values. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_patient_timeline.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_patient_timeline.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_patient_timeline.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_patient_timeline.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADAE <- tmc_ex_adae ADSL <- tmc_ex_adsl %>% filter(USUBJID %in% ADAE$USUBJID) ADCM <- tmc_ex_adcm %>% mutate( CMSTDY = case_when( CMCAT == \"medcl B\" ~ 20, CMCAT == \"medcl C\" ~ 150, TRUE ~ 1 ) %>% with_label(\"Study Day of Start of Medication\"), CMENDY = case_when( CMCAT == \"medcl B\" ~ 700, CMCAT == \"medcl C\" ~ 1000, TRUE ~ 500 ) %>% with_label(\"Study Day of End of Medication\"), CMASTDTM = ASTDTM, CMAENDTM = AENDTM ) }) join_keys(data) <- default_cdisc_join_keys[c(\"ADSL\", \"ADAE\", \"ADCM\")] adcm_keys <- c(\"STUDYID\", \"USUBJID\", \"ASTDTM\", \"CMSEQ\", \"ATC1\", \"ATC2\", \"ATC3\", \"ATC4\") join_keys(data)[\"ADCM\", \"ADCM\"] <- adcm_keys join_keys(data)[\"ADAE\", \"ADCM\"] <- c(\"STUDYID\", \"USUBJID\") app <- init( data = data, modules = modules( tm_g_pp_patient_timeline( label = \"Patient Timeline\", dataname_adae = \"ADAE\", dataname_adcm = \"ADCM\", parentname = \"ADSL\", patient_col = \"USUBJID\", plot_height = c(600L, 200L, 2000L), cmdecod = choices_selected( choices = variable_choices(data[[\"ADCM\"]], \"CMDECOD\"), selected = \"CMDECOD\", ), aeterm = choices_selected( choices = variable_choices(data[[\"ADAE\"]], \"AETERM\"), selected = c(\"AETERM\") ), aetime_start = choices_selected( choices = variable_choices(data[[\"ADAE\"]], \"ASTDTM\"), selected = c(\"ASTDTM\") ), aetime_end = choices_selected( choices = variable_choices(data[[\"ADAE\"]], \"AENDTM\"), selected = c(\"AENDTM\") ), dstime_start = choices_selected( choices = variable_choices(data[[\"ADCM\"]], \"CMASTDTM\"), selected = c(\"CMASTDTM\") ), dstime_end = choices_selected( choices = variable_choices(data[[\"ADCM\"]], \"CMAENDTM\"), selected = c(\"CMAENDTM\") ), aerelday_start = choices_selected( choices = variable_choices(data[[\"ADAE\"]], \"ASTDY\"), selected = c(\"ASTDY\") ), aerelday_end = choices_selected( choices = variable_choices(data[[\"ADAE\"]], \"AENDY\"), selected = c(\"AENDY\") ), dsrelday_start = choices_selected( choices = variable_choices(data[[\"ADCM\"]], \"ASTDY\"), selected = c(\"ASTDY\") ), dsrelday_end = choices_selected( choices = variable_choices(data[[\"ADCM\"]], \"AENDY\"), selected = c(\"AENDY\") ) ) ) ) #> Initializing tm_g_pp_patient_timeline #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_therapy.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"module produces patient profile therapy table ggplot2::ggplot() type plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_therapy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"","code":"tm_g_pp_therapy( label, dataname = \"ADCM\", parentname = \"ADSL\", patient_col = \"USUBJID\", atirel = NULL, cmdecod = NULL, cmindc = NULL, cmdose = NULL, cmtrt = NULL, cmdosu = NULL, cmroute = NULL, cmdosfrq = NULL, cmstdy = NULL, cmendy = NULL, font_size = c(12L, 12L, 25L), plot_height = c(700L, 200L, 2000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_therapy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. atirel (teal.transform::choices_selected()) object available choices preselected option ATIREL variable dataname. cmdecod (teal.transform::choices_selected()) object available choices preselected option CMDECOD variable dataname. cmindc (teal.transform::choices_selected()) object available choices preselected option CMINDC variable dataname. cmdose (teal.transform::choices_selected()) object available choices preselected option CMDOSE variable dataname. cmtrt (teal.transform::choices_selected()) object available choices preselected option CMTRT variable dataname. cmdosu (teal.transform::choices_selected()) object available choices preselected option CMDOSU variable dataname. cmroute (teal.transform::choices_selected()) object available choices preselected option CMROUTE variable dataname. cmdosfrq (teal.transform::choices_selected()) object available choices preselected option CMDOSFRQ variable dataname. cmstdy (teal.transform::choices_selected()) object available choices preselected option CMSTDY variable dataname. cmendy (teal.transform::choices_selected()) object available choices preselected option CMENDY variable dataname. font_size (numeric) numeric vector length 3 current, minimum maximum font size values. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_therapy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_therapy.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"module generates following objects, can modified place using decorators:: plot (ggplot2) table (listing_df - output rlistings::as_listing) Decorators can applied outputs specific objects using named list teal_transform_module objects. \"default\" name reserved decorators applied outputs. See code snippet : additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":"tm_g_pp_therapy( ..., # arguments for module decorators = list( default = list(teal_transform_module(...)), # applied to all outputs plot = list(teal_transform_module(...)), # applied only to `plot` output table = list(teal_transform_module(...)) # applied only to `table` output ) )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_therapy.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_therapy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADCM <- tmc_ex_adcm ADSL <- tmc_ex_adsl %>% filter(USUBJID %in% ADCM$USUBJID) ADCM$CMASTDTM <- ADCM$ASTDTM ADCM$CMAENDTM <- ADCM$AENDTM }) join_keys(data) <- default_cdisc_join_keys[c(\"ADSL\", \"ADCM\")] adcm_keys <- c(\"STUDYID\", \"USUBJID\", \"ASTDTM\", \"CMSEQ\", \"ATC1\", \"ATC2\", \"ATC3\", \"ATC4\") join_keys(data)[\"ADCM\", \"ADCM\"] <- adcm_keys ADSL <- data[[\"ADSL\"]] ADCM <- data[[\"ADCM\"]] app <- init( data = data, modules = modules( tm_g_pp_therapy( label = \"Therapy\", dataname = \"ADCM\", parentname = \"ADSL\", patient_col = \"USUBJID\", plot_height = c(600L, 200L, 2000L), atirel = choices_selected( choices = variable_choices(ADCM, \"ATIREL\"), selected = c(\"ATIREL\") ), cmdecod = choices_selected( choices = variable_choices(ADCM, \"CMDECOD\"), selected = \"CMDECOD\" ), cmindc = choices_selected( choices = variable_choices(ADCM, \"CMINDC\"), selected = \"CMINDC\" ), cmdose = choices_selected( choices = variable_choices(ADCM, \"CMDOSE\"), selected = \"CMDOSE\" ), cmtrt = choices_selected( choices = variable_choices(ADCM, \"CMTRT\"), selected = \"CMTRT\" ), cmdosu = choices_selected( choices = variable_choices(ADCM, \"CMDOSU\"), selected = c(\"CMDOSU\") ), cmroute = choices_selected( choices = variable_choices(ADCM, \"CMROUTE\"), selected = \"CMROUTE\" ), cmdosfrq = choices_selected( choices = variable_choices(ADCM, \"CMDOSFRQ\"), selected = \"CMDOSFRQ\" ), cmstdy = choices_selected( choices = variable_choices(ADCM, \"ASTDY\"), selected = \"ASTDY\" ), cmendy = choices_selected( choices = variable_choices(ADCM, \"AENDY\"), selected = \"AENDY\" ) ) ) ) #> Initializing tm_g_pp_therapy #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_vitals.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"module produces patient profile vitals ggplot2::ggplot() type plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_vitals.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"","code":"tm_g_pp_vitals( label, dataname = \"ADVS\", parentname = \"ADSL\", patient_col = \"USUBJID\", paramcd = NULL, aval = lifecycle::deprecated(), aval_var = NULL, xaxis = NULL, font_size = c(12L, 12L, 25L), plot_height = c(700L, 200L, 2000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_vitals.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. aval Please use aval_var argument instead. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. xaxis (teal.transform::choices_selected()) object available choices preselected option time variable dataname put plot x-axis. font_size (numeric) numeric vector length 3 current, minimum maximum font size values. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_vitals.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_vitals.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"plot supports horizontal lines following 6 PARAMCD levels present dataname: \"SYSBP\", \"DIABP\", \"TEMP\", \"RESP\", \"OXYSAT\".","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_vitals.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_vitals.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_g_pp_vitals.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"","code":"library(nestcolor) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADVS <- tmc_ex_advs }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADVS <- data[[\"ADVS\"]] app <- init( data = data, modules = modules( tm_g_pp_vitals( label = \"Vitals\", dataname = \"ADVS\", parentname = \"ADSL\", patient_col = \"USUBJID\", plot_height = c(600L, 200L, 2000L), paramcd = choices_selected( choices = variable_choices(ADVS, \"PARAMCD\"), selected = \"PARAMCD\" ), xaxis = choices_selected( choices = variable_choices(ADVS, \"ADY\"), selected = \"ADY\" ), aval_var = choices_selected( choices = variable_choices(ADVS, \"AVAL\"), selected = \"AVAL\" ) ) ) ) #> Initializing tm_g_pp_vitals #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Abnormality Summary Table — tm_t_abnormality","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"module produces table summarize abnormality.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"","code":"tm_t_abnormality( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, by_vars, grade, abnormal = list(low = c(\"LOW\", \"LOW LOW\"), high = c(\"HIGH\", \"HIGH HIGH\")), id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"USUBJID\"), selected = \"USUBJID\", fixed = TRUE), baseline_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"BNRIND\"), selected = \"BNRIND\", fixed = TRUE), treatment_flag_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"ONTRTFL\"), selected = \"ONTRTFL\", fixed = TRUE), treatment_flag = teal.transform::choices_selected(\"Y\"), add_total = TRUE, total_label = default_total_label(), exclude_base_abn = FALSE, drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, na_level = default_na_str(), basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. by_vars (teal.transform::choices_selected()) object available choices preselected option variable names used split summary rows. grade (teal.transform::choices_selected()) object available choices preselected option variable names can used specify abnormality grade. Variable must factor. abnormal (named list) defined user indicate abnormalities displayed. id_var (teal.transform::choices_selected()) object specifying variable name subject id. baseline_var (teal.transform::choices_selected()) variable baseline abnormality grade. treatment_flag_var (teal.transform::choices_selected()) treatment flag variable. treatment_flag (teal.transform::choices_selected()) value indicating treatment records treatment_flag_var. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). exclude_base_abn (logical) whether exclude patients abnormal values baseline. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. na_level (character) NA level input dataset, default \"\". basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"Patients abnormality baseline treatment visit can excluded accordance GDSR specifications using exclude_base_abn.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"module generates following objects, can modified place using decorators: table (ElementaryTable - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb %>% mutate( ONTRTFL = case_when( AVISIT %in% c(\"SCREENING\", \"BASELINE\") ~ \"\", TRUE ~ \"Y\" ) %>% with_label(\"On Treatment Record Flag\") ) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_t_abnormality( label = \"Abnormality Table\", dataname = \"ADLB\", arm_var = choices_selected( choices = variable_choices(ADSL, subset = c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), add_total = FALSE, by_vars = choices_selected( choices = variable_choices(ADLB, subset = c(\"LBCAT\", \"PARAM\", \"AVISIT\")), selected = c(\"LBCAT\", \"PARAM\"), keep_order = TRUE ), baseline_var = choices_selected( variable_choices(ADLB, subset = \"BNRIND\"), selected = \"BNRIND\", fixed = TRUE ), grade = choices_selected( choices = variable_choices(ADLB, subset = \"ANRIND\"), selected = \"ANRIND\", fixed = TRUE ), abnormal = list(low = \"LOW\", high = \"HIGH\"), exclude_base_abn = FALSE ) ) ) #> Initializing tm_t_abnormality #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality_by_worst_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"module produces table summarize laboratory test results highest grade post-baseline","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality_by_worst_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"","code":"tm_t_abnormality_by_worst_grade( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"USUBJID\"), selected = \"USUBJID\", fixed = TRUE), paramcd, atoxgr_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"ATOXGR\"), selected = \"ATOXGR\", fixed = TRUE), worst_high_flag_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"WGRHIFL\"), selected = \"WGRHIFL\", fixed = TRUE), worst_low_flag_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"WGRLOFL\"), selected = \"WGRLOFL\", fixed = TRUE), worst_flag_indicator = teal.transform::choices_selected(\"Y\"), add_total = TRUE, total_label = default_total_label(), drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality_by_worst_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. id_var (teal.transform::choices_selected()) object specifying variable name subject id. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. atoxgr_var (teal.transform::choices_selected()) object available choices preselected option variable names can used Analysis Toxicity Grade. worst_high_flag_var (teal.transform::choices_selected()) object available choices preselected option variable names can used Worst High Grade flag. worst_low_flag_var (teal.transform::choices_selected()) object available choices preselected option variable names can used Worst Low Grade flag. worst_flag_indicator (teal.transform::choices_selected()) value indicating worst grade. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality_by_worst_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality_by_worst_grade.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"module generates following objects, can modified place using decorators: table (ElementaryTable - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality_by_worst_grade.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_abnormality_by_worst_grade.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb %>% filter(!AVISIT %in% c(\"SCREENING\", \"BASELINE\")) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_t_abnormality_by_worst_grade( label = \"Laboratory Test Results with Highest Grade Post-Baseline\", dataname = \"ADLB\", arm_var = choices_selected( choices = variable_choices(ADSL, subset = c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), paramcd = choices_selected( choices = value_choices(ADLB, \"PARAMCD\", \"PARAM\"), selected = c(\"ALT\", \"CRP\", \"IGA\") ), add_total = FALSE ) ), filter = teal_slices( teal_slice(\"ADSL\", \"SAFFL\", selected = \"Y\"), teal_slice(\"ADLB\", \"ONTRTFL\", selected = \"Y\") ) ) #> Initializing tm_t_abnormality_by_worst_grade #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_ancova.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: ANCOVA Summary — tm_t_ancova","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"module produces table summarize analysis variance, consistent TLG Catalog template AOVT01 available multiple endpoints selected.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_ancova.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"","code":"tm_t_ancova( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, arm_ref_comp = NULL, aval_var, cov_var, include_interact = FALSE, interact_var = NULL, interact_y = FALSE, avisit, paramcd, conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_ancova.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. cov_var (teal.transform::choices_selected()) object available choices preselected option covariates variables. include_interact (logical) whether interaction term included model. interact_var (character) name variable interactions arm. interaction needed, default option NULL. interact_y (character) selected item interact_var column used select specific ANCOVA results interact_var discrete. interaction needed, default option FALSE. avisit (teal.transform::choices_selected()) value analysis visit AVISIT interest. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_ancova.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_ancova.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"single endpoint selected, unadjusted adjusted comparison provided. modules expects analysis data following variables: AVISIT: variable used filter analysis visits. PARAMCD: variable used filter endpoints, filtering paramcd avisit, one observation per patient expected analysis meaningful.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_ancova.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"module generates following objects, can modified place using decorators: table (ElementaryTable - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_ancova.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_ancova.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADQS <- tmc_ex_adqs }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADQS <- data[[\"ADQS\"]] arm_ref_comp <- list( ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ), ACTARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ) ) app <- init( data = data, modules = modules( tm_t_ancova( label = \"ANCOVA Table\", dataname = \"ADQS\", avisit = choices_selected( choices = value_choices(ADQS, \"AVISIT\"), selected = \"WEEK 1 DAY 8\" ), arm_var = choices_selected( choices = variable_choices(ADSL, c(\"ARM\", \"ACTARMCD\", \"ARMCD\")), selected = \"ARMCD\" ), arm_ref_comp = arm_ref_comp, aval_var = choices_selected( choices = variable_choices(ADQS, c(\"CHG\", \"AVAL\")), selected = \"CHG\" ), cov_var = choices_selected( choices = variable_choices(ADQS, c(\"BASE\", \"STRATA1\", \"SEX\")), selected = \"STRATA1\" ), paramcd = choices_selected( choices = value_choices(ADQS, \"PARAMCD\", \"PARAM\"), selected = \"FKSI-FWB\" ), interact_var = choices_selected( choices = variable_choices(ADQS, c(\"BASE\", \"STRATA1\", \"SEX\")), selected = \"STRATA1\" ) ) ) ) #> Initializing tm_t_ancova #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_binary_outcome.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Binary Outcome Table — tm_t_binary_outcome","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"module produces binary outcome response summary table, option match template response table RSPT01 available TLG Catalog .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_binary_outcome.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"","code":"tm_t_binary_outcome( label, dataname, parentname = ifelse(test = inherits(arm_var, \"data_extract_spec\"), yes = teal.transform::datanames_input(arm_var), no = \"ADSL\"), arm_var, arm_ref_comp = NULL, paramcd, strata_var, aval_var = teal.transform::choices_selected(choices = teal.transform::variable_choices(dataname, c(\"AVALC\", \"SEX\")), selected = \"AVALC\", fixed = FALSE), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), default_responses = c(\"CR\", \"PR\", \"Y\", \"Complete Response (CR)\", \"Partial Response (PR)\", \"M\"), rsp_table = FALSE, control = list(global = list(method = ifelse(rsp_table, \"clopper-pearson\", \"waldcc\"), conf_level = 0.95), unstrat = list(method_ci = ifelse(rsp_table, \"wald\", \"waldcc\"), method_test = \"schouten\", odds = TRUE), strat = list(method_ci = \"cmh\", method_test = \"cmh\")), add_total = FALSE, total_label = default_total_label(), na_level = default_na_str(), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_binary_outcome.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. strata_var (teal.transform::choices_selected()) names variables stratified analysis. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). default_responses (list character) defines default codes response variable module per value paramcd. passed vector transmitted paramcd values. passed list must named contain arrays, name corresponding single value paramcd. array may contain default response values named arrays rsp default selected response values levels default level choices. rsp_table (logical) whether initial set-module match RSPT01. Defaults FALSE. control (named list) named list containing 3 named lists follows: global: list settings overall analysis 2 named elements method conf_level. unstrat: list settings unstratified analysis 3 named elements method_ci method_test, odds. See tern::estimate_proportion_diff(), tern::test_proportion_diff(), tern::estimate_odds_ratio(), respectively, options details settings implemented analysis. strat: list settings stratified analysis elements method_ci method_test. See tern::estimate_proportion_diff() tern::test_proportion_diff(), respectively, options details settings implemented analysis. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_binary_outcome.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_binary_outcome.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"display order response categories inherits factor level order source data. Use base::factor() levels argument manipulate source data order include/exclude re-categorize response categories arrange display order. response categories \"Missing\", \"Evaluable (NE)\", \"Missing unevaluable\", 95% confidence interval calculated. Reference arms automatically combined multiple arms selected reference group.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_binary_outcome.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_binary_outcome.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_binary_outcome.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADRS <- tmc_ex_adrs %>% mutate( AVALC = d_onco_rsp_label(AVALC) %>% with_label(\"Character Result/Finding\") ) %>% filter(PARAMCD != \"OVRINV\" | AVISIT == \"FOLLOW UP\") }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADRS <- data[[\"ADRS\"]] arm_ref_comp <- list( ARMCD = list(ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\")), ARM = list(ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\")) ) app <- init( data = data, modules = modules( tm_t_binary_outcome( label = \"Responders\", dataname = \"ADRS\", paramcd = choices_selected( choices = value_choices(ADRS, \"PARAMCD\", \"PARAM\"), selected = \"BESRSPI\" ), arm_var = choices_selected( choices = variable_choices(ADRS, c(\"ARM\", \"ARMCD\", \"ACTARMCD\")), selected = \"ARM\" ), arm_ref_comp = arm_ref_comp, strata_var = choices_selected( choices = variable_choices(ADRS, c(\"SEX\", \"BMRKR2\", \"RACE\")), selected = \"RACE\" ), default_responses = list( BESRSPI = list( rsp = c(\"Complete Response (CR)\", \"Partial Response (PR)\"), levels = c( \"Complete Response (CR)\", \"Partial Response (PR)\", \"Stable Disease (SD)\", \"Progressive Disease (PD)\" ) ), INVET = list( rsp = c(\"Stable Disease (SD)\", \"Not Evaluable (NE)\"), levels = c( \"Complete Response (CR)\", \"Not Evaluable (NE)\", \"Partial Response (PR)\", \"Progressive Disease (PD)\", \"Stable Disease (SD)\" ) ), OVRINV = list( rsp = c(\"Progressive Disease (PD)\", \"Stable Disease (SD)\"), levels = c(\"Progressive Disease (PD)\", \"Stable Disease (SD)\", \"Not Evaluable (NE)\") ) ) ) ) ) #> Initializing tm_t_binary_outcome #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_coxreg.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Cox Regression Model — tm_t_coxreg","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"module fits Cox univariable multi-variable models, consistent TLG Catalog templates Cox regression tables COXT01 COXT02, respectively. See TLG Catalog entries COXT01 COXT02 .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_coxreg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"","code":"tm_t_coxreg( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, arm_ref_comp = NULL, paramcd, cov_var, strata_var, aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVAL\"), \"AVAL\", fixed = TRUE), cnsr_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"CNSR\"), \"CNSR\", fixed = TRUE), multivariate = TRUE, na_level = default_na_str(), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_coxreg.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. cov_var (teal.transform::choices_selected()) object available choices preselected option covariates variables. strata_var (teal.transform::choices_selected()) names variables stratified analysis. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. cnsr_var (teal.transform::choices_selected()) object available choices preselected option censoring variable. multivariate (logical) FALSE, univariable approach used instead multi-variable model. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_coxreg.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_coxreg.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"Cox Proportional Hazards (PH) model commonly used method estimate magnitude effect survival analysis. assumes proportional hazards: ratio hazards groups (e.g., two arms) constant time. ratio referred \"hazard ratio\" (HR) one commonly reported metrics describe effect size survival analysis. modules expects analysis data following variables: AVAL: time event CNSR: 1 record AVAL censored, 0 otherwise PARAMCD: variable used filter endpoint (e.g. OS). filtering PARAMCD one observation per patient expected arm variables stratification/covariate variables taken ADSL data.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_coxreg.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"likelihood ratio test supported models include strata - Wald test substituted cases. Multi-variable default choice backward compatibility.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_coxreg.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"module generates following objects, can modified place using decorators: table (TableTree created rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_coxreg.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"example-1 Open Shinylive example-2 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_coxreg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"","code":"## First example ## ============= ## The example below is based on the usual approach involving creation of ## a random CDISC dataset and then running the application. arm_ref_comp <- list( ACTARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ), ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ) ) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADTTE <- tmc_ex_adtte }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADTTE <- data[[\"ADTTE\"]] app <- init( data = data, modules = modules( tm_t_coxreg( label = \"Cox Reg.\", dataname = \"ADTTE\", arm_var = choices_selected(c(\"ARM\", \"ARMCD\", \"ACTARMCD\"), \"ARM\"), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( value_choices(ADTTE, \"PARAMCD\", \"PARAM\"), \"OS\" ), strata_var = choices_selected( c(\"COUNTRY\", \"STRATA1\", \"STRATA2\"), \"STRATA1\" ), cov_var = choices_selected( c(\"AGE\", \"BMRKR1\", \"BMRKR2\", \"REGION1\"), \"AGE\" ), multivariate = TRUE ) ) ) #> Initializing tm_t_coxreg #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) } ## Second example ## ============== ## This time, a synthetic pair of ADTTE/ADSL data is fabricated for Cox regression ## where ties and pval_method matter. library(dplyr) data <- teal_data() data <- within(data, { ADTTE <- data.frame( STUDYID = \"LUNG\", AVAL = c(4, 3, 1, 1, 2, 2, 3, 1, 2), CNSR = c(1, 1, 1, 0, 1, 1, 0, 0, 0), ARMCD = factor( c(0, 1, 1, 1, 1, 0, 0, 0, 0), labels = c(\"ARM A\", \"ARM B\") ), SEX = factor( c(0, 0, 0, 0, 1, 1, 1, 1, 1), labels = c(\"F\", \"M\") ), INST = factor(c(\"A\", \"A\", \"B\", \"B\", \"A\", \"B\", \"A\", \"B\", \"A\")), stringsAsFactors = FALSE ) ADTTE <- rbind(ADTTE, ADTTE, ADTTE, ADTTE) ADTTE <- as_tibble(ADTTE) set.seed(1) ADTTE$INST <- sample(ADTTE$INST) ADTTE$AGE <- sample(seq(5, 75, 5), size = nrow(ADTTE), replace = TRUE) ADTTE$USUBJID <- paste(\"sub\", 1:nrow(ADTTE), ADTTE$INST, sep = \"-\") ADTTE$PARAM <- ADTTE$PARAMCD <- \"OS\" ADSL <- subset( ADTTE, select = c(\"USUBJID\", \"STUDYID\", \"ARMCD\", \"SEX\", \"INST\", \"AGE\") ) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADTTE <- data[[\"ADTTE\"]] ## `teal` application ## ---------------- ## Note that the R code exported by `Show R Code` does not include the data ## pre-processing. You will need to create the dataset as above before ## running the exported R code. arm_ref_comp <- list(ARMCD = list(ref = \"ARM A\", comp = c(\"ARM B\"))) app <- init( data = data, modules = modules( tm_t_coxreg( label = \"Cox Reg.\", dataname = \"ADTTE\", arm_var = choices_selected(c(\"ARMCD\"), \"ARMCD\"), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( value_choices(ADTTE, \"PARAMCD\", \"PARAM\"), \"OS\" ), strata_var = choices_selected(c(\"INST\"), NULL), cov_var = choices_selected(c(\"SEX\", \"AGE\"), \"SEX\"), multivariate = TRUE ) ) ) #> Initializing tm_t_coxreg #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Events by Term — tm_t_events","title":"teal Module: Events by Term — tm_t_events","text":"module produces table events term.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Events by Term — tm_t_events","text":"","code":"tm_t_events( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, hlt, llt, add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), event_type = \"event\", sort_criteria = c(\"freq_desc\", \"alpha\"), sort_freq_col = total_label, prune_freq = 0, prune_diff = 0, drop_arm_levels = TRUE, incl_overall_sum = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Events by Term — tm_t_events","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. hlt (teal.transform::choices_selected()) name variable high level term events. llt (teal.transform::choices_selected()) name variable low level term events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). event_type (character) type event summarized (e.g. adverse event, treatment). Default \"event\". sort_criteria (character) sort final table. Default option freq_desc sorts column sort_freq_col decreasing number patients event. Alternative option alpha sorts events alphabetically. sort_freq_col (character) column sort frequency sort_criteria set freq_desc. prune_freq (number) threshold use trimming table using event incidence rate column. prune_diff (number) threshold use trimming table using criteria difference rates two columns. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. incl_overall_sum (flag) whether two rows summarize overall number adverse events included top table. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Events by Term — tm_t_events","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Events by Term — tm_t_events","text":"module generates following objects, can modified place using decorators: table (TableTree created rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Events by Term — tm_t_events","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Events by Term — tm_t_events","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADAE <- tmc_ex_adae }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADAE <- data[[\"ADAE\"]] app <- init( data = data, modules = modules( tm_t_events( label = \"Adverse Event Table\", dataname = \"ADAE\", arm_var = choices_selected(c(\"ARM\", \"ARMCD\"), \"ARM\"), llt = choices_selected( choices = variable_choices(ADAE, c(\"AETERM\", \"AEDECOD\")), selected = c(\"AEDECOD\") ), hlt = choices_selected( choices = variable_choices(ADAE, c(\"AEBODSYS\", \"AESOC\")), selected = \"AEBODSYS\" ), add_total = TRUE, event_type = \"adverse event\" ) ) ) #> Initializing tm_t_events #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_by_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Events by Grade — tm_t_events_by_grade","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"module produces table summarize events grade.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_by_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"","code":"tm_t_events_by_grade( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, hlt, llt, grade, grading_groups = list(`Any Grade (%)` = c(\"1\", \"2\", \"3\", \"4\", \"5\"), `Grade 1-2 (%)` = c(\"1\", \"2\"), `Grade 3-4 (%)` = c(\"3\", \"4\"), `Grade 5 (%)` = \"5\"), col_by_grade = FALSE, prune_freq = 0, prune_diff = 0, add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_by_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. hlt (teal.transform::choices_selected()) name variable high level term events. llt (teal.transform::choices_selected()) name variable low level term events. grade (character) name severity level variable. grading_groups (list) named list grading groups used col_by_grade = TRUE. col_by_grade (logical) whether display grading groups nested columns. prune_freq (number) threshold use trimming table using event incidence rate column. prune_diff (number) threshold use trimming table using criteria difference rates two columns. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_by_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_by_grade.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"module generates following objects, can modified place using decorators: table (TableTree created rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_by_grade.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_by_grade.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl .lbls_adae <- col_labels(tmc_ex_adae) ADAE <- tmc_ex_adae %>% mutate_if(is.character, as.factor) #' be certain of having factors col_labels(ADAE) <- .lbls_adae }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADAE <- data[[\"ADAE\"]] app <- init( data = data, modules = modules( tm_t_events_by_grade( label = \"Adverse Events by Grade Table\", dataname = \"ADAE\", arm_var = choices_selected(c(\"ARM\", \"ARMCD\"), \"ARM\"), llt = choices_selected( choices = variable_choices(ADAE, c(\"AETERM\", \"AEDECOD\")), selected = c(\"AEDECOD\") ), hlt = choices_selected( choices = variable_choices(ADAE, c(\"AEBODSYS\", \"AESOC\")), selected = \"AEBODSYS\" ), grade = choices_selected( choices = variable_choices(ADAE, c(\"AETOXGR\", \"AESEV\")), selected = \"AETOXGR\" ) ) ) ) #> Initializing tm_t_events_by_grade #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_patyear.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"module produces table event rates adjusted patient-years.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_patyear.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"","code":"tm_t_events_patyear( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, events_var, paramcd, aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVAL\"), \"AVAL\", fixed = TRUE), avalu_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALU\"), \"AVALU\", fixed = TRUE), add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_patyear.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. events_var (teal.transform::choices_selected()) object available choices preselected option variable event counts. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. avalu_var (teal.transform::choices_selected()) object available choices preselected option analysis unit variable. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_patyear.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_patyear.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"module generates following objects, can modified place using decorators: table (TableTree created rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_patyear.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"example-1 Open Shinylive example-2 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_patyear.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADAETTE <- tmc_ex_adaette %>% filter(PARAMCD %in% c(\"AETTE1\", \"AETTE2\", \"AETTE3\")) %>% mutate(is_event = CNSR == 0) %>% mutate(n_events = as.integer(is_event)) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADAETTE <- data[[\"ADAETTE\"]] # 1. Basic Example app <- init( data = data, modules = modules( tm_t_events_patyear( label = \"AE Rate Adjusted for Patient-Years At Risk Table\", dataname = \"ADAETTE\", arm_var = choices_selected( choices = variable_choices(ADSL, c(\"ARM\", \"ARMCD\")), selected = \"ARMCD\" ), add_total = TRUE, events_var = choices_selected( choices = variable_choices(ADAETTE, \"n_events\"), selected = \"n_events\", fixed = TRUE ), paramcd = choices_selected( choices = value_choices(ADAETTE, \"PARAMCD\", \"PARAM\"), selected = \"AETTE1\" ) ) ) ) #> Initializing tm_t_events_patyear #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) } # 2. Example with table split on 2 arm_var variables app <- init( data = data, modules = modules( tm_t_events_patyear( label = \"AE Rate Adjusted for Patient-Years At Risk Table\", dataname = \"ADAETTE\", arm_var = choices_selected( choices = variable_choices(ADSL, c(\"ARM\", \"ARMCD\", \"SEX\")), selected = c(\"ARM\", \"SEX\") ), add_total = TRUE, events_var = choices_selected( choices = variable_choices(ADAETTE, \"n_events\"), selected = \"n_events\", fixed = TRUE ), paramcd = choices_selected( choices = value_choices(ADAETTE, \"PARAMCD\", \"PARAM\"), selected = \"AETTE1\" ) ) ) ) #> Initializing tm_t_events_patyear #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_summary.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Adverse Events Summary — tm_t_events_summary","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"module produces adverse events summary table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_summary.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"","code":"tm_t_events_summary( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, flag_var_anl = NULL, flag_var_aesi = NULL, dthfl_var = teal.transform::choices_selected(teal.transform::variable_choices(parentname, \"DTHFL\"), \"DTHFL\", fixed = TRUE), dcsreas_var = teal.transform::choices_selected(teal.transform::variable_choices(parentname, \"DCSREAS\"), \"DCSREAS\", fixed = TRUE), llt = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AEDECOD\"), \"AEDECOD\", fixed = TRUE), aeseq_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AESEQ\"), \"AESEQ\", fixed = TRUE), add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), count_dth = TRUE, count_wd = TRUE, count_subj = TRUE, count_pt = TRUE, count_events = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_summary.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. flag_var_anl (teal.transform::choices_selected() NULL) vector names flag variables dataset used count adverse event sub-groups (e.g. Serious events, Related events, etc.). Variable labels used table row names exist. flag_var_aesi (teal.transform::choices_selected() NULL) vector names flag variables dataset used count adverse event special interest groups. flag variables must type logical. Variable labels used table row names exist. dthfl_var (teal.transform::choices_selected()) object available choices preselected option variable names can used death flag variable. Records `\"Y\"“ summarized table row \"Total number deaths\". dcsreas_var (teal.transform::choices_selected()) object available choices preselected option variable names can used study discontinuation reason variable. Records \"ADVERSE EVENTS\" summarized table row \"Total number patients withdrawn study due AE\". llt (teal.transform::choices_selected()) name variable low level term events. aeseq_var (teal.transform::choices_selected()) variable adverse events sequence number dataset. Used counting total number events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). count_dth (logical) whether show count total deaths (based dthfl_var). Defaults TRUE. count_wd (logical) whether show count patients withdrawn study due adverse event (based dcsreas_var). Defaults TRUE. count_subj (logical) whether show count unique subjects (based USUBJID). applies event flag variables provided. count_pt (logical) whether show count unique preferred terms (based llt). applies event flag variables provided. count_events (logical) whether show count events (based aeseq_var). applies event flag variables provided. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_summary.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_summary.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"module generates following objects, can modified place using decorators: table (TableTree created rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_summary.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_events_summary.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl %>% mutate( DTHFL = case_when( !is.na(DTHDT) ~ \"Y\", TRUE ~ \"\" ) %>% with_label(\"Subject Death Flag\") ) ADAE <- tmc_ex_adae .add_event_flags <- function(dat) { dat <- dat %>% mutate( TMPFL_SER = AESER == \"Y\", TMPFL_REL = AEREL == \"Y\", TMPFL_GR5 = AETOXGR == \"5\", TMP_SMQ01 = !is.na(SMQ01NAM), TMP_SMQ02 = !is.na(SMQ02NAM), TMP_CQ01 = !is.na(CQ01NAM) ) column_labels <- list( TMPFL_SER = \"Serious AE\", TMPFL_REL = \"Related AE\", TMPFL_GR5 = \"Grade 5 AE\", TMP_SMQ01 = aesi_label(dat[[\"SMQ01NAM\"]], dat[[\"SMQ01SC\"]]), TMP_SMQ02 = aesi_label(\"Y.9.9.9.9/Z.9.9.9.9 AESI\"), TMP_CQ01 = aesi_label(dat[[\"CQ01NAM\"]]) ) col_labels(dat)[names(column_labels)] <- as.character(column_labels) dat } #' Generating user-defined event flags. ADAE <- ADAE %>% .add_event_flags() .ae_anl_vars <- names(ADAE)[startsWith(names(ADAE), \"TMPFL_\")] .aesi_vars <- names(ADAE)[startsWith(names(ADAE), \"TMP_\")] }) join_keys(data) <- default_cdisc_join_keys[names(data)] app <- init( data = data, modules = modules( tm_t_events_summary( label = \"Adverse Events Summary\", dataname = \"ADAE\", arm_var = choices_selected( choices = variable_choices(\"ADSL\", c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), flag_var_anl = choices_selected( choices = variable_choices(\"ADAE\", data[[\".ae_anl_vars\"]]), selected = data[[\".ae_anl_vars\"]][1], keep_order = TRUE, fixed = FALSE ), flag_var_aesi = choices_selected( choices = variable_choices(\"ADAE\", data[[\".aesi_vars\"]]), selected = data[[\".aesi_vars\"]][1], keep_order = TRUE, fixed = FALSE ), add_total = TRUE ) ) ) #> Initializing tm_t_events_summary #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_exposure.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"module produces exposure table risk management plan.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_exposure.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"","code":"tm_t_exposure( label, dataname, parentname = ifelse(inherits(col_by_var, \"data_extract_spec\"), teal.transform::datanames_input(col_by_var), \"ADSL\"), row_by_var, col_by_var, paramcd = teal.transform::choices_selected(choices = teal.transform::value_choices(dataname, \"PARAMCD\", \"PARAM\"), selected = \"TDURD\"), paramcd_label = \"PARAM\", id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"USUBJID\"), selected = \"USUBJID\", fixed = TRUE), parcat, aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"AVAL\"), selected = \"AVAL\", fixed = TRUE), avalu_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"AVALU\"), selected = \"AVALU\", fixed = TRUE), add_total, total_label = default_total_label(), add_total_row = TRUE, total_row_label = \"Total number of patients and patient time*\", na_level = default_na_str(), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_exposure.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. row_by_var (teal.transform::choices_selected()) object available choices preselected option variable names can used split rows. col_by_var (teal.transform::choices_selected()) object available choices preselected option variable names can used split columns. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. paramcd_label (character) column dataset value used label argument paramcd. id_var (teal.transform::choices_selected()) object specifying variable name subject id. parcat (teal.transform::choices_selected()) object available choices preselected option parameter category values. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. avalu_var (teal.transform::choices_selected()) object available choices preselected option analysis unit variable. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). add_total_row (flag) whether \"total\" level added others includes levels constitute split. custom label can set level via total_row_label argument. total_row_label (character) string display total row label row enabled (see add_total_row). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_exposure.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_exposure.html","id":"decorating-modules","dir":"Reference","previous_headings":"","what":"Decorating Modules","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"module generates following objects, can modified place using decorators: table (TableTree created rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_exposure.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_exposure.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADEX <- tmc_ex_adex set.seed(1, kind = \"Mersenne-Twister\") .labels <- col_labels(ADEX, fill = FALSE) ADEX <- ADEX %>% distinct(USUBJID, .keep_all = TRUE) %>% mutate( PARAMCD = \"TDURD\", PARAM = \"Overall duration (days)\", AVAL = sample(x = seq(1, 200), size = n(), replace = TRUE), AVALU = \"Days\" ) %>% bind_rows(ADEX) col_labels(ADEX) <- .labels }) join_keys(data) <- default_cdisc_join_keys[names(data)] app <- init( data = data, modules = modules( tm_t_exposure( label = \"Duration of Exposure Table\", dataname = \"ADEX\", paramcd = choices_selected( choices = value_choices(data[[\"ADEX\"]], \"PARAMCD\", \"PARAM\"), selected = \"TDURD\" ), col_by_var = choices_selected( choices = variable_choices(data[[\"ADEX\"]], subset = c(\"SEX\", \"ARM\")), selected = \"SEX\" ), row_by_var = choices_selected( choices = variable_choices(data[[\"ADEX\"]], subset = c(\"RACE\", \"REGION1\", \"STRATA1\", \"SEX\")), selected = \"RACE\" ), parcat = choices_selected( choices = value_choices(data[[\"ADEX\"]], \"PARCAT2\"), selected = \"Drug A\" ), add_total = FALSE ) ), filter = teal_slices(teal_slice(\"ADSL\", \"SAFFL\", selected = \"Y\")) ) #> Initializing tm_t_exposure #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_logistic.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Logistic Regression — tm_t_logistic","title":"teal Module: Logistic Regression — tm_t_logistic","text":"module produces multi-variable logistic regression table consistent TLG Catalog template LGRT02 available .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_logistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Logistic Regression — tm_t_logistic","text":"","code":"tm_t_logistic( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var = NULL, arm_ref_comp = NULL, paramcd, cov_var = NULL, avalc_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALC\"), \"AVALC\", fixed = TRUE), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_logistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Logistic Regression — tm_t_logistic","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected() NULL) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. NULL, arm/treatment variable included logistic model. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. cov_var (teal.transform::choices_selected()) object available choices preselected option covariates variables. avalc_var (teal.transform::choices_selected()) object available choices preselected option analysis variable (categorical). conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_logistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Logistic Regression — tm_t_logistic","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_logistic.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Logistic Regression — tm_t_logistic","text":"module generates following objects, can modified place using decorators: table (ElementaryTable - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_logistic.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Logistic Regression — tm_t_logistic","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_logistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Logistic Regression — tm_t_logistic","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADRS <- tmc_ex_adrs %>% filter(PARAMCD %in% c(\"BESRSPI\", \"INVET\")) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADRS <- data[[\"ADRS\"]] arm_ref_comp <- list( ACTARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ), ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ) ) app <- init( data = data, modules = modules( tm_t_logistic( label = \"Logistic Regression\", dataname = \"ADRS\", arm_var = choices_selected( choices = variable_choices(ADRS, c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( choices = value_choices(ADRS, \"PARAMCD\", \"PARAM\"), selected = \"BESRSPI\" ), cov_var = choices_selected( choices = c(\"SEX\", \"AGE\", \"BMRKR1\", \"BMRKR2\"), selected = \"SEX\" ) ) ) ) #> Initializing tm_t_logistic #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_mult_events.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Multiple Events by Term — tm_t_mult_events","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"module produces table multiple events term.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_mult_events.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"","code":"tm_t_mult_events( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, seq_var, hlt, llt, add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), event_type = \"event\", drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_mult_events.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. seq_var (teal.transform::choices_selected()) object available choices preselected option variable names can used analysis sequence number variable. Used counting unique number events. hlt (teal.transform::choices_selected()) name variable high level term events. llt (teal.transform::choices_selected()) name variable low level term events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). event_type (character) type event summarized (e.g. adverse event, treatment). Default \"event\". drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_mult_events.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_mult_events.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_mult_events.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_mult_events.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADCM <- tmc_ex_adcm }) join_keys(data) <- default_cdisc_join_keys[names(data)] adcm_keys <- c(\"STUDYID\", \"USUBJID\", \"ASTDTM\", \"CMSEQ\", \"ATC1\", \"ATC2\", \"ATC3\", \"ATC4\") join_keys(data)[\"ADCM\", \"ADCM\"] <- adcm_keys ADSL <- data[[\"ADSL\"]] ADCM <- data[[\"ADCM\"]] app <- init( data = data, modules = modules( tm_t_mult_events( label = \"Concomitant Medications by Medication Class and Preferred Name\", dataname = \"ADCM\", arm_var = choices_selected(c(\"ARM\", \"ARMCD\"), \"ARM\"), seq_var = choices_selected(\"CMSEQ\", selected = \"CMSEQ\", fixed = TRUE), hlt = choices_selected( choices = variable_choices(ADCM, c(\"ATC1\", \"ATC2\", \"ATC3\", \"ATC4\")), selected = c(\"ATC1\", \"ATC2\", \"ATC3\", \"ATC4\") ), llt = choices_selected( choices = variable_choices(ADCM, c(\"CMDECOD\")), selected = c(\"CMDECOD\") ), add_total = TRUE, event_type = \"treatment\" ) ) ) #> Initializing tm_t_mult_events #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_basic_info.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"module produces patient profile basic info report using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_basic_info.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"","code":"tm_t_pp_basic_info( label, dataname = \"ADSL\", patient_col = \"USUBJID\", vars = NULL, pre_output = NULL, post_output = NULL, decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_basic_info.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. patient_col (character) name patient ID variable. vars (teal.transform::choices_selected()) object available choices preselected option variables dataname show table. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_basic_info.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_basic_info.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"module generates following objects, can modified place using decorators: table (listing_df - output rlistings::as_listing) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_basic_info.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_basic_info.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] app <- init( data = data, modules = modules( tm_t_pp_basic_info( label = \"Basic Info\", dataname = \"ADSL\", patient_col = \"USUBJID\", vars = choices_selected( choices = variable_choices(ADSL), selected = c(\"ARM\", \"AGE\", \"SEX\", \"COUNTRY\", \"RACE\", \"EOSSTT\") ) ) ) ) #> Initializing tm_t_pp_basic_info #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_laboratory.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"module produces patient profile laboratory table using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_laboratory.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"","code":"tm_t_pp_laboratory( label, dataname = \"ADLB\", parentname = \"ADSL\", patient_col = \"USUBJID\", timepoints = NULL, aval = lifecycle::deprecated(), aval_var = NULL, avalu = lifecycle::deprecated(), avalu_var = NULL, param = NULL, paramcd = NULL, anrind = NULL, pre_output = NULL, post_output = NULL, decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_laboratory.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. timepoints (teal.transform::choices_selected()) object available choices preselected option time variable dataname. aval Please use aval_var argument instead. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. avalu Please use avalu_var argument instead. avalu_var (teal.transform::choices_selected()) object available choices preselected option analysis unit variable. param (teal.transform::choices_selected()) object available choices preselected option PARAM variable dataname. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. anrind (teal.transform::choices_selected()) object available choices preselected option ANRIND variable dataname. Variable following 3 levels: \"HIGH\", \"LOW\", \"NORMAL\". pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_laboratory.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_laboratory.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"module generates following objects, can modified place using decorators: table (listing_df - output rlistings::as_listing) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_laboratory.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_laboratory.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_t_pp_laboratory( label = \"Vitals\", dataname = \"ADLB\", patient_col = \"USUBJID\", paramcd = choices_selected( choices = variable_choices(ADLB, \"PARAMCD\"), selected = \"PARAMCD\" ), param = choices_selected( choices = variable_choices(ADLB, \"PARAM\"), selected = \"PARAM\" ), timepoints = choices_selected( choices = variable_choices(ADLB, \"ADY\"), selected = \"ADY\" ), anrind = choices_selected( choices = variable_choices(ADLB, \"ANRIND\"), selected = \"ANRIND\" ), aval_var = choices_selected( choices = variable_choices(ADLB, \"AVAL\"), selected = \"AVAL\" ), avalu_var = choices_selected( choices = variable_choices(ADLB, \"AVALU\"), selected = \"AVALU\" ) ) ) ) #> Initializing tm_t_pp_laboratory #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_medical_history.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"module produces patient profile medical history report using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_medical_history.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"","code":"tm_t_pp_medical_history( label, dataname = \"ADMH\", parentname = \"ADSL\", patient_col = \"USUBJID\", mhterm = NULL, mhbodsys = NULL, mhdistat = NULL, pre_output = NULL, post_output = NULL, decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_medical_history.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. mhterm (teal.transform::choices_selected()) object available choices preselected option MHTERM variable dataname. mhbodsys (teal.transform::choices_selected()) object available choices preselected option MHBODSYS variable dataname. mhdistat (teal.transform::choices_selected()) object available choices preselected option MHDISTAT variable dataname. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_medical_history.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_medical_history.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_medical_history.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_medical_history.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADMH <- tmc_ex_admh }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADMH <- data[[\"ADMH\"]] app <- init( data = data, modules = modules( tm_t_pp_medical_history( label = \"Medical History\", dataname = \"ADMH\", parentname = \"ADSL\", patient_col = \"USUBJID\", mhterm = choices_selected( choices = variable_choices(ADMH, c(\"MHTERM\")), selected = \"MHTERM\" ), mhbodsys = choices_selected( choices = variable_choices(ADMH, \"MHBODSYS\"), selected = \"MHBODSYS\" ), mhdistat = choices_selected( choices = variable_choices(ADMH, \"MHDISTAT\"), selected = \"MHDISTAT\" ) ) ) ) #> Initializing tm_t_pp_medical_history #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_prior_medication.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"module produces patient profile prior medication report using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_prior_medication.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"","code":"tm_t_pp_prior_medication( label, dataname = \"ADCM\", parentname = \"ADSL\", patient_col = \"USUBJID\", atirel = NULL, cmdecod = NULL, cmindc = NULL, cmstdy = NULL, pre_output = NULL, post_output = NULL, decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_prior_medication.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. atirel (teal.transform::choices_selected()) object available choices preselected option ATIREL variable dataname. cmdecod (teal.transform::choices_selected()) object available choices preselected option CMDECOD variable dataname. cmindc (teal.transform::choices_selected()) object available choices preselected option CMINDC variable dataname. cmstdy (teal.transform::choices_selected()) object available choices preselected option CMSTDY variable dataname. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_prior_medication.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_prior_medication.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"module generates following objects, can modified place using decorators: table (listing_df - output rlistings::as_listing) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_prior_medication.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_pp_prior_medication.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADCM <- tmc_ex_adcm ADSL <- tmc_ex_adsl %>% filter(USUBJID %in% ADCM$USUBJID) ADCM$CMASTDTM <- ADCM$ASTDTM ADCM$CMAENDTM <- ADCM$AENDTM }) join_keys(data) <- default_cdisc_join_keys[names(data)] adcm_keys <- c(\"STUDYID\", \"USUBJID\", \"ASTDTM\", \"CMSEQ\", \"ATC1\", \"ATC2\", \"ATC3\", \"ATC4\") join_keys(data)[\"ADCM\", \"ADCM\"] <- adcm_keys ADSL <- data[[\"ADSL\"]] ADCM <- data[[\"ADCM\"]] app <- init( data = data, modules = modules( tm_t_pp_prior_medication( label = \"Prior Medication\", dataname = \"ADCM\", parentname = \"ADSL\", patient_col = \"USUBJID\", atirel = choices_selected( choices = variable_choices(ADCM, \"ATIREL\"), selected = \"ATIREL\" ), cmdecod = choices_selected( choices = variable_choices(ADCM, \"CMDECOD\"), selected = \"CMDECOD\" ), cmindc = choices_selected( choices = variable_choices(ADCM, \"CMINDC\"), selected = \"CMINDC\" ), cmstdy = choices_selected( choices = variable_choices(ADCM, \"ASTDY\"), selected = \"ASTDY\" ) ) ) ) #> Initializing tm_t_pp_prior_medication #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Shift by Arm — tm_t_shift_by_arm","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"module produces summary table analysis indicator levels arm.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"","code":"tm_t_shift_by_arm( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, paramcd, visit_var, aval_var, base_var = lifecycle::deprecated(), baseline_var, treatment_flag_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"ONTRTFL\"), selected = \"ONTRTFL\"), treatment_flag = teal.transform::choices_selected(\"Y\"), useNA = c(\"ifany\", \"no\"), na_level = default_na_str(), add_total = FALSE, total_label = default_total_label(), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. visit_var (teal.transform::choices_selected()) object available choices preselected option variable names can used visit variable. Must factor dataname. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. base_var Please use baseline_var argument instead. baseline_var (teal.transform::choices_selected()) object available choices preselected option variable values can used baseline_var. treatment_flag_var (teal.transform::choices_selected()) treatment flag variable. treatment_flag (teal.transform::choices_selected()) value indicating treatment records treatment_flag_var. useNA (character) whether missing data (NA) displayed level. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). add_total (logical) whether include row total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADEG <- tmc_ex_adeg }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADEG <- data[[\"ADEG\"]] app <- init( data = data, modules = modules( tm_t_shift_by_arm( label = \"Shift by Arm Table\", dataname = \"ADEG\", arm_var = choices_selected( variable_choices(ADSL, subset = c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), paramcd = choices_selected( value_choices(ADEG, \"PARAMCD\"), selected = \"HR\" ), visit_var = choices_selected( value_choices(ADEG, \"AVISIT\"), selected = \"POST-BASELINE MINIMUM\" ), aval_var = choices_selected( variable_choices(ADEG, subset = \"ANRIND\"), selected = \"ANRIND\", fixed = TRUE ), baseline_var = choices_selected( variable_choices(ADEG, subset = \"BNRIND\"), selected = \"BNRIND\", fixed = TRUE ), useNA = \"ifany\" ) ) ) #> Initializing tm_t_shift_by_arm #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm_by_worst.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"module produces summary table worst analysis indicator variable level per subject arm.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm_by_worst.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"","code":"tm_t_shift_by_arm_by_worst( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, paramcd, aval_var, base_var = lifecycle::deprecated(), baseline_var, worst_flag_var, worst_flag, treatment_flag_var = teal.transform::choices_selected(choices = teal.transform::variable_choices(dataname, subset = \"ONTRTFL\"), selected = \"ONTRTFL\"), treatment_flag = teal.transform::choices_selected(\"Y\"), useNA = c(\"ifany\", \"no\"), na_level = default_na_str(), add_total = FALSE, total_label = default_total_label(), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm_by_worst.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. base_var Please use baseline_var argument instead. baseline_var (teal.transform::choices_selected()) object available choices preselected option variable values can used baseline_var. worst_flag_var (teal.transform::choices_selected()) object available choices preselected option variable names can used worst flag variable. worst_flag (character) value indicating worst analysis indicator level. treatment_flag_var (teal.transform::choices_selected()) treatment flag variable. treatment_flag (teal.transform::choices_selected()) value indicating treatment records treatment_flag_var. useNA (character) whether missing data (NA) displayed level. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). add_total (logical) whether include row total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm_by_worst.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm_by_worst.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm_by_worst.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_arm_by_worst.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADEG <- tmc_ex_adeg }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADEG <- data[[\"ADEG\"]] app <- init( data = data, modules = modules( tm_t_shift_by_arm_by_worst( label = \"Shift by Arm Table\", dataname = \"ADEG\", arm_var = choices_selected( variable_choices(ADSL, subset = c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), paramcd = choices_selected( value_choices(ADEG, \"PARAMCD\"), selected = \"ECGINTP\" ), worst_flag_var = choices_selected( variable_choices(ADEG, c(\"WORS02FL\", \"WORS01FL\")), selected = \"WORS02FL\" ), worst_flag = choices_selected( value_choices(ADEG, \"WORS02FL\"), selected = \"Y\", fixed = TRUE ), aval_var = choices_selected( variable_choices(ADEG, c(\"AVALC\", \"ANRIND\")), selected = \"AVALC\" ), baseline_var = choices_selected( variable_choices(ADEG, c(\"BASEC\", \"BNRIND\")), selected = \"BASEC\" ), useNA = \"ifany\" ) ) ) #> Initializing tm_t_shift_by_arm_by_worst #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Grade Summary Table — tm_t_shift_by_grade","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"module produces summary table worst grades per subject visit parameter.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"","code":"tm_t_shift_by_grade( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, visit_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"AVISIT\"), selected = \"AVISIT\", fixed = TRUE), paramcd, worst_flag_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = c(\"WGRLOVFL\", \"WGRLOFL\", \"WGRHIVFL\", \"WGRHIFL\")), selected = \"WGRLOVFL\"), worst_flag_indicator = teal.transform::choices_selected(teal.transform::value_choices(dataname, \"WGRLOVFL\"), selected = \"Y\", fixed = TRUE), anl_toxgrade_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = c(\"ATOXGR\")), selected = c(\"ATOXGR\"), fixed = TRUE), base_toxgrade_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = c(\"BTOXGR\")), selected = c(\"BTOXGR\"), fixed = TRUE), id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"USUBJID\"), selected = \"USUBJID\", fixed = TRUE), add_total = FALSE, total_label = default_total_label(), drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, na_level = default_na_str(), code_missing_baseline = FALSE, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. visit_var (teal.transform::choices_selected()) object available choices preselected option variable names can used visit variable. Must factor dataname. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. worst_flag_var (teal.transform::choices_selected()) object available choices preselected option variable names can used worst flag variable. worst_flag_indicator (teal.transform::choices_selected()) value indicating worst grade. anl_toxgrade_var (teal.transform::choices_selected()) variable analysis toxicity grade. base_toxgrade_var (teal.transform::choices_selected()) variable baseline toxicity grade. id_var (teal.transform::choices_selected()) object specifying variable name subject id. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). code_missing_baseline (logical) whether missing baseline grades counted grade 0. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_grade.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_grade.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_shift_by_grade.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_t_shift_by_grade( label = \"Grade Laboratory Abnormality Table\", dataname = \"ADLB\", arm_var = choices_selected( choices = variable_choices(ADSL, subset = c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), paramcd = choices_selected( choices = value_choices(ADLB, \"PARAMCD\", \"PARAM\"), selected = \"ALT\" ), worst_flag_var = choices_selected( choices = variable_choices(ADLB, subset = c(\"WGRLOVFL\", \"WGRLOFL\", \"WGRHIVFL\", \"WGRHIFL\")), selected = c(\"WGRLOVFL\") ), worst_flag_indicator = choices_selected( value_choices(ADLB, \"WGRLOVFL\"), selected = \"Y\", fixed = TRUE ), anl_toxgrade_var = choices_selected( choices = variable_choices(ADLB, subset = c(\"ATOXGR\")), selected = c(\"ATOXGR\"), fixed = TRUE ), base_toxgrade_var = choices_selected( choices = variable_choices(ADLB, subset = c(\"BTOXGR\")), selected = c(\"BTOXGR\"), fixed = TRUE ), add_total = FALSE ) ), filter = teal_slices(teal_slice(\"ADSL\", \"SAFFL\", selected = \"Y\")) ) #> Initializing tm_t_shift_by_grade #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_smq.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"module produces adverse events table Standardized MedDRA Query.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_smq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"","code":"tm_t_smq( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"USUBJID\"), selected = \"USUBJID\", fixed = TRUE), llt, add_total = TRUE, total_label = default_total_label(), sort_criteria = c(\"freq_desc\", \"alpha\"), drop_arm_levels = TRUE, na_level = default_na_str(), smq_varlabel = \"Standardized MedDRA Query\", baskets, scopes, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_smq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. id_var (teal.transform::choices_selected()) object specifying variable name subject id. llt (teal.transform::choices_selected()) name variable low level term events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). sort_criteria (character) sort final table. Default option freq_desc sorts column sort_freq_col decreasing number patients event. Alternative option alpha sorts events alphabetically. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). smq_varlabel (character) label use new column SMQ created tern::h_stack_by_baskets(). baskets (teal.transform::choices_selected()) object available choices preselected options standardized/customized queries. scopes (teal.transform::choices_selected()) object available choices scopes standardized queries. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_smq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_smq.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_smq.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_smq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADAE <- tmc_ex_adae .names_baskets <- grep(\"^(SMQ|CQ).*NAM$\", names(ADAE), value = TRUE) .names_scopes <- grep(\"^SMQ.*SC$\", names(ADAE), value = TRUE) .cs_baskets <- choices_selected( choices = variable_choices(ADAE, subset = .names_baskets), selected = .names_baskets ) .cs_scopes <- choices_selected( choices = variable_choices(ADAE, subset = .names_scopes), selected = .names_scopes, fixed = TRUE ) }) join_keys(data) <- default_cdisc_join_keys[names(data)] app <- init( data = data, modules = modules( tm_t_smq( label = \"Adverse Events by SMQ Table\", dataname = \"ADAE\", arm_var = choices_selected( choices = variable_choices(data[[\"ADSL\"]], subset = c(\"ARM\", \"SEX\")), selected = \"ARM\" ), add_total = FALSE, baskets = data[[\".cs_baskets\"]], scopes = data[[\".cs_scopes\"]], llt = choices_selected( choices = variable_choices(data[[\"ADAE\"]], subset = c(\"AEDECOD\")), selected = \"AEDECOD\" ) ) ) ) #> Initializing tm_t_smq #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Summary of Variables — tm_t_summary","title":"teal Module: Summary of Variables — tm_t_summary","text":"module produces table summarize variables.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Summary of Variables — tm_t_summary","text":"","code":"tm_t_summary( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, summarize_vars, add_total = TRUE, total_label = default_total_label(), show_arm_var_labels = TRUE, useNA = c(\"ifany\", \"no\"), na_level = default_na_str(), numeric_stats = c(\"n\", \"mean_sd\", \"mean_ci\", \"median\", \"median_ci\", \"quantiles\", \"range\", \"geom_mean\"), denominator = c(\"N\", \"n\", \"omit\"), drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Summary of Variables — tm_t_summary","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. summarize_vars (teal.transform::choices_selected()) names variables summarized. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). show_arm_var_labels (flag) whether arm variable label(s) displayed. Defaults TRUE. useNA (character) whether missing data (NA) displayed level. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). numeric_stats (character) names statistics display numeric summary variables. Available statistics n, mean_sd, mean_ci, median, median_ci, quantiles, range, geom_mean. denominator (character) chooses percentages calculated. option N, reference population column total used denominator. option n, number non-missing records row column intersection used denominator. omit chosen, percentage omitted. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Summary of Variables — tm_t_summary","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Summary of Variables — tm_t_summary","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Summary of Variables — tm_t_summary","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Summary of Variables — tm_t_summary","text":"","code":"# Preparation of the test case - use `EOSDY` and `DCSREAS` variables to demonstrate missing data. data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADSL$EOSDY[1] <- NA_integer_ }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] app <- init( data = data, modules = modules( tm_t_summary( label = \"Demographic Table\", dataname = \"ADSL\", arm_var = choices_selected(c(\"ARM\", \"ARMCD\"), \"ARM\"), add_total = TRUE, summarize_vars = choices_selected( c(\"SEX\", \"RACE\", \"BMRKR2\", \"EOSDY\", \"DCSREAS\", \"AGE\"), c(\"SEX\", \"RACE\") ), useNA = \"ifany\" ) ) ) #> Initializing tm_t_summary #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary_by.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"module produces table summarize variables row groups.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary_by.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"","code":"tm_t_summary_by( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, by_vars, summarize_vars, id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"USUBJID\"), selected = \"USUBJID\", fixed = TRUE), paramcd = NULL, add_total = TRUE, total_label = default_total_label(), parallel_vars = FALSE, row_groups = FALSE, useNA = c(\"ifany\", \"no\"), na_level = default_na_str(), numeric_stats = c(\"n\", \"mean_sd\", \"median\", \"range\"), denominator = teal.transform::choices_selected(c(\"n\", \"N\", \"omit\"), \"omit\", fixed = TRUE), drop_arm_levels = TRUE, drop_zero_levels = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary_by.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. by_vars (teal.transform::choices_selected()) object available choices preselected option variable names used split summary rows. summarize_vars (teal.transform::choices_selected()) names variables summarized. id_var (teal.transform::choices_selected()) object specifying variable name subject id. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). parallel_vars (logical) whether summarized variables arranged columns. Can set TRUE chosen analysis variables numeric. row_groups (logical) whether summarized variables arranged row groups. useNA (character) whether missing data (NA) displayed level. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). numeric_stats (character) names statistics display numeric summary variables. Available statistics n, mean_sd, mean_ci, median, median_ci, quantiles, range, geom_mean. denominator (character) chooses percentages calculated. option N, reference population column total used denominator. option n, number non-missing records row column intersection used denominator. omit chosen, percentage omitted. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. drop_zero_levels (logical) whether rows zero counts columns removed table. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary_by.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary_by.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary_by.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_summary_by.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_t_summary_by( label = \"Summary by Row Groups Table\", dataname = \"ADLB\", arm_var = choices_selected( choices = variable_choices(ADSL, c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), add_total = TRUE, by_vars = choices_selected( choices = variable_choices(ADLB, c(\"PARAM\", \"AVISIT\")), selected = c(\"AVISIT\") ), summarize_vars = choices_selected( choices = variable_choices(ADLB, c(\"AVAL\", \"CHG\")), selected = c(\"AVAL\") ), useNA = \"ifany\", paramcd = choices_selected( choices = value_choices(ADLB, \"PARAMCD\", \"PARAM\"), selected = \"ALT\" ) ) ) ) #> Initializing tm_t_summary_by #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_tte.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Time-To-Event Table — tm_t_tte","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"module produces time--event analysis summary table, consistent TLG Catalog template TTET01 available .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_tte.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"","code":"tm_t_tte( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, arm_ref_comp = NULL, paramcd, strata_var, aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVAL\"), \"AVAL\", fixed = TRUE), cnsr_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"CNSR\"), \"CNSR\", fixed = TRUE), conf_level_coxph = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), conf_level_survfit = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), time_points, time_unit_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALU\"), \"AVALU\", fixed = TRUE), event_desc_var = teal.transform::choices_selected(\"EVNTDESC\", \"EVNTDESC\", fixed = TRUE), add_total = FALSE, total_label = default_total_label(), na_level = default_na_str(), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_tte.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. strata_var (teal.transform::choices_selected()) names variables stratified analysis. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. cnsr_var (teal.transform::choices_selected()) object available choices preselected option censoring variable. conf_level_coxph (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). conf_level_survfit (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). time_points (teal.transform::choices_selected()) object available choices preselected option time points can used tern::surv_timepoint(). time_unit_var (teal.transform::choices_selected()) object available choices pre-selected option time unit variable. event_desc_var (character teal.transform::data_extract_spec()) variable name event description information, optional. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_tte.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_tte.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"core functionality module based tern::coxph_pairwise(), tern::surv_timepoint(), tern::surv_time() tern package. arm stratification variables taken parentname data. following variables used module: AVAL: time event CNSR: 1 record AVAL censored, 0 otherwise PARAMCD: variable used filter endpoint (e.g. OS). filtering PARAMCD one observation per patient expected","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_tte.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_tte.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/tm_t_tte.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADTTE <- tmc_ex_adtte }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADTTE <- data[[\"ADTTE\"]] arm_ref_comp <- list( ACTARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ), ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ) ) app <- init( data = data, modules = modules( tm_t_tte( label = \"Time To Event Table\", dataname = \"ADTTE\", arm_var = choices_selected( variable_choices(ADSL, c(\"ARM\", \"ARMCD\", \"ACTARMCD\")), \"ARM\" ), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( value_choices(ADTTE, \"PARAMCD\", \"PARAM\"), \"OS\" ), strata_var = choices_selected( variable_choices(ADSL, c(\"SEX\", \"BMRKR2\")), \"SEX\" ), time_points = choices_selected(c(182, 243), 182), event_desc_var = choices_selected( variable_choices(ADTTE, \"EVNTDESC\"), \"EVNTDESC\", fixed = TRUE ) ) ) ) #> Initializing tm_t_tte #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/validate_arm.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if vector is valid as to be used as a treatment arm variable — validate_arm","title":"Check if vector is valid as to be used as a treatment arm variable — validate_arm","text":"Check vector valid used treatment arm variable","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/validate_arm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if vector is valid as to be used as a treatment arm variable — validate_arm","text":"","code":"validate_arm(arm_vec)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/validate_arm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if vector is valid as to be used as a treatment arm variable — validate_arm","text":"arm_vec vector validated","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/validate_arm.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check if vector is valid as to be used as a treatment arm variable — validate_arm","text":"validate error returned vector factor detailed error message entries empty strings","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/validate_standard_inputs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Validate standard input values for a teal module — validate_standard_inputs","text":"","code":"validate_standard_inputs( adsl, adslvars = character(0), anl, anlvars = character(0), need_arm = TRUE, arm_var, ref_arm, comp_arm, min_n_levels_armvar = 1L, max_n_levels_armvar = 100L, min_nrow = 1 )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/reference/validate_standard_inputs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Validate standard input values for a teal module — validate_standard_inputs","text":"adsl data.frame subject-level data adslvars required variables ADSL anl data.frame analysis data anlvars required variables ANL need_arm flag indicating whether grouping variable arm_var required can optionally NULL. arm_var character name grouping variable, typically arm ref_arm character name reference level arm_var comp_arm character name comparison level arm_var min_n_levels_armvar minimum number levels grouping variable arm_var. Defaults 1, NULL minimum. max_n_levels_armvar maximum number levels grouping variable arm_var. Use NULL maximum. min_nrow minimum number observations ADSL ANL","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"enhancements-0-9-1-9042","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.9.1.9042","text":"Added teal.logger functionality logging changes shiny inputs modules. Introduced ylim parameter tm_g_km module controls width y-axis. Added functionality tm_t_events_patyear split columns multiple (nested) variables via arm_var argument. Added arguments arm_var_labels template_summary show_arm_var_labels tm_t_summary allow user display arm variable (arm_var) labels table header. Added argument stats modules tm_g_forest_rsp tm_g_forest_tte allow users specify statistics include table. Added argument riskdiff modules tm_g_forest_rsp tm_g_forest_tte allow users add risk difference table column. Added count_dth count_wd parameters tm_t_events_summary select/deselect “Total number deaths” “Total number patients withdrawn study due AE” rows, respectively. options correspond “Count deaths” “Count withdrawals due AE” checkboxes available module run.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-9-1-9042","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.9.1.9042","text":"Removed Show Warnings modals modules. Clarified documentation specifying whether multiple values can selected arm_var argument module. Replaced use rtables::add_colcounts() function show_colcounts argument basic_table(). Began deprecation cycle show_labels argument template_summary effect tm_t_summary module. Replaced instances deprecated strata argument tern::control_lineplot_vars() group_var.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"bug-fixes-0-9-1-9042","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.9.1.9042","text":"Fixed bug creating modules delayed_data teal.transform::all_choices.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"tealmodulesclinical-091","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.9.1","title":"teal.modules.clinical 0.9.1","text":"CRAN release: 2024-04-27","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"enhancements-0-9-1","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.9.1","text":"Updated tm_g_forest_rsp tm_g_forest_tte use refactored version g_forest. Plots now displayed ggplot objects instead grob objects. Added parameters font_size rel_width_forest control font size width plot relative table, respectively. Updated tm_t_summary_by allow NULL input paramcd argument. Updated tm_g_km use refactored version g_km. Plots now displayed ggplot objects instead grob objects. Added parameters rel_height_plot, font_size, control_annot_surv_med, control_annot_coxph control height plot relative table, font size, median survival time table size, Cox-PH table size, respectively. Added control argument tm_t_binary_outcome control settings analysis (methods, confidence intervals, odds ratios) within module.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-9-1","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.9.1","text":"Replaced instances deprecated na_level argument tern functions na_str. Replaced argument/list element name strata instead strat tern function calls following deprecation argument/name within tern. Removed formatters dependencies replaced use functions relating variable labels functions teal.data.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"tealmodulesclinical-090","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.9.0","title":"teal.modules.clinical 0.9.0","text":"CRAN release: 2024-02-23","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"breaking-changes-0-9-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"teal.modules.clinical 0.9.0","text":"Adapted modules use teal_data objects. Module arguments previously accepted inputs teal.transform::choices_selected() teal.transform::data_extract_spec() now accept input teal.transform::choices_selected(). affected modules : tm_a_gee, tm_a_mmrm, tm_g_ci, tm_g_forest_rsp, tm_g_forest_tte, tm_g_ipp, tm_g_km, tm_g_lineplot, tm_g_pp_adverse_events, tm_g_pp_patient_timeline, tm_g_pp_therapy, tm_g_pp_vitals, tm_t_abnormality, tm_t_abnormality_by_worst_grade, tm_t_ancova, tm_t_binary_outcome, tm_t_coxreg, tm_t_events, tm_t_events_by_grade, tm_t_events_patyear, tm_t_events_summary, tm_t_exposure, tm_t_logistic, tm_t_mult_events, tm_t_pp_basic_info, tm_t_pp_laboratory, tm_t_pp_medical_history, tm_t_pp_prior_medication, tm_t_shift_by_arm, tm_t_shift_by_arm_by_worst, tm_t_shift_by_grade, tm_t_smq, tm_t_summary, tm_t_summary_by, tm_t_tte","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"enhancements-0-9-0","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.9.0","text":"Updated documentation vignettes demonstrate method pass teal_data object teal::init(). Simplify examples vignettes code removing package prefixes possible. Added parameter sort_freq_col tm_t_events allow user select column use sorting decreasing frequency. Added parameter incl_overall_sum tm_t_events allow user choose whether overall summary rows included top table. Updated documentation vignettes demonstrate method pass teal_data object teal::init(). Added default_total_label set_default_total_label functions get set default total column label (total_label) modules. Implemented tern::default_na_str tern::set_default_na_str functions get set default missing value replacement string (na_level) modules.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"bug-fixes-0-9-0","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.9.0","text":"Fixed bug tm_g_lineplot forcing module initialize table. Fixes partial matching.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-9-0","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.9.0","text":"Deprecated aval argument tm_t_pp_laboratory tm_g_pp_vitals replaced aval_var argument. Deprecated avalu argument tm_t_pp_laboratory replaced avalu_var argument. Deprecated base_var argument tm_g_ipp, tm_t_shift_by_arm, template_shift_by_arm_by_worst replaced baseline_var argument. Specified minimal version package dependencies. Replaced usage deprecated summarize_vars function analyze_vars. Reduced package dependencies (removed tidyr, rlang, magrittr styler). Introduced tests partial matching.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"enhancements-0-8-16","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.16","text":"Added informative error message grade mapping error occurs tm_t_abnormality_by_worst_grade. Fixed label indentation tm_t_abnormality_by_worst_grade. Added total_label argument enable customization “Patients” column/row label following modules: tm_a_mmrm, tm_t_abnormality, tm_t_abnormality_by_worst_grade, tm_t_binary_outcome, tm_t_events, tm_t_events_by_grade, tm_t_events_patyear, tm_t_events_summary, tm_t_exposure, tm_t_mult_events, tm_t_shift_by_arm, tm_t_shift_by_arm_worst, tm_t_shift_by_grade, tm_t_smq, tm_t_summary, tm_t_summary_by, tm_t_tte. Increased default width tm_g_forest_tte plot prevent overlapping text. Improved default annotation table sizing tm_g_km. Refactored tm_t_exposure display “total” row last row table instead summary row. Added parameters add_total_row set whether total row displayed total_row_label set total row label. Updated tm_t_events maintain indentation pruning. Updated default reference/comparison arm level selection work arm variable levels filtered . Updated tm_t_coxreg drop factor covariate variable levels present avoid errors filtering. Updated tm_t_pp_basic_info, tm_t_pp_medical_history, tm_g_pp_therapy, tm_g_pp_adverse_events, tm_t_pp_laboratory print patient ID table. Updated tm_t_pp_basic_info, tm_g_pp_therapy, tm_g_pp_adverse_events, tm_t_pp_laboratory use rlistings print data neatly reports. Updated tm_g_lineplot allow user remove interval plot. Updated documentation vignettes demonstrate method pass teal_data object teal::init().","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"bug-fixes-0-8-16","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.16","text":"Fixed bug tm_t_coxreg preventing table displayed covariates selected.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-8-16","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.16","text":"Updated control_incidence_rate parameter names tm_t_events_patyear time_unit_input time_unit_output input_time_unit num_pt_year, respectively, parameter names changed tern. Hid datasets used patient profile modules filter panel. Replaced datanames = \"\" parameter datasets used internally module.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"breaking-changes-0-8-15","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"teal.modules.clinical 0.8.15","text":"Replaced chunks simpler qenv class. Replaced datasets argument containing FilteredData new arguments data (tdata object) filter_panel_api (FilterPanelAPI).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"enhancements-0-8-15","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.15","text":"Replaced synthetic_cdisc_data refactored synthetic_cdisc_dataset function speed dataset loading tests/examples. Added new GEE module tm_a_gee. Added interface selecting interaction term tm_t_ancova. Updated encoding input checks use shinyvalidate::InputValidator better UI experience. Previously used shiny::validate. Added option tm_a_mmrm allow Kenward-Roger adjustments standard errors p-values. Added option choose facet scale options tm_g_barchart_simple. Added label parameter cs_to_select_spec/cs_to_des_select cs_to_filter_spec/cs_to_des_filter allow user customize label printed selection field. Updated tm_t_coxreg module refactoring summarize_coxreg tern fix indentation. Updated tm_t_exposure module use new function analyze_patients_exposure_in_cols fix table structure.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"bug-fixes-0-8-15","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.15","text":"Fixed bug causing overlapping bars tm_g_barchart_simple. Fixed bug figures svg format. Fixed bug tm_t_summary tm_t_summary_by preventing users specifying numeric_stats argument.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-8-15","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.15","text":"Updated package Suggests use scda.2022 rather scda.2021. Removed unused argument param tm_g_pp_vitals. Removed optimizer choice tm_a_mmrm since can always use automatically determined optimizer. Created datasets use examples/tests adsl, adae, adaette, adcm, adeg, adex, adlb, admh, adqs, adrs, adtte, advs. datasets stored data folder accessible via tmc_ex_* prefix. Updated examples tests use datasets teal.modules.clinical package instead scda datasets. Updated tests use testthat 3rd edition replaced applicable tests snapshot testing. Implemented lubridate package date variables internal data. Changed default value plot_width tm_g_forest_rsp prevent clutter.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"enhancements-0-8-14","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.14","text":"Updated synthetic data tests version rcd_2022_02_28. Updated test files tests/testthat/ synthetic_cdisc_data(\"2022_02_28\") Reverted missing data checkbox tm_t_summary (encoding filtering separate). Implemented new widget allows dragging dropping select comparison groups. Added teal.reporter functionality modules. Enhanced tm_t_pp_medical_history module use table_with_settings module return rtables object. Implemented nestcolor examples, refactored tm_g_barchart_simple allow use nestcolor. Added descriptive title/labels visit name subtitle tm_g_ci. Updated tm_a_mmrm column name deselecting treatment “obs” “Patients”, added subtitles footnotes. Added title parameter category subtitle tm_t_exposure, cleaned labels. Added titles worse flag variable subtitles tm_t_shift_by_grade tm_t_shift_by_arm_by_worst. Added footnote tm_t_events_patyear CI method. Added subtitle footnotes tm_g_km. Added Stratified Analysis CI method option panel tm_t_binary_outcome. Added validation covariate/visit conflicts tm_a_mmrm. Remove unnecessary brackets header tm_t_exposure. Hid footnotes tm_g_km tm_t_tte “Compare Treatments” .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"bug-fixes-0-8-14","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.14","text":"Fixed bug tm_g_barchart_simple prevented display graph. Fixed broken example tm_t_abnormality_by_worst_grade. Fixed bug tm_a_mmrm prevented table headers displaying. Fixed bug tm_g_forest_rsp deselecting endpoint. Fixed bug tm_t_binary_outcome crashed app deselecting paramcd. Fixed teal.reporter card names tm_t_smq. Fixed bug tm_t_shift_by_arm_by_worst adding validations choosing different endpoint values. Fixed bug tm_t_coxreg preventing footnotes displaying univariate models.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-8-14","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.14","text":"Added nestcolor dependency replaced deprecated function tern::color_palette nestcolor::color_palette.","code":""},{"path":[]},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"tm_g_pp_adverse_events-0-8-13","dir":"Changelog","previous_headings":"Enhancements","what":"tm_g_pp_adverse_events","title":"teal.modules.clinical 0.8.13","text":"Updated position labels. Updated plot render color legend.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"tm_t_summary_by-0-8-13","dir":"Changelog","previous_headings":"Enhancements","what":"tm_t_summary_by","title":"teal.modules.clinical 0.8.13","text":"Enhanced module support geometric mean encoding panel.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"tm_t_summary-0-8-13","dir":"Changelog","previous_headings":"Enhancements","what":"tm_t_summary","title":"teal.modules.clinical 0.8.13","text":"Updated added footnote. Enhanced module support geometric mean encoding panel. Updated module display checkboxes numeric variables statistics numeric variables part selected. Updated validations warn users using dataset non unique identifiers selecting variables non supported types (.e. Date, POSIXt). Added checkbox remove column generated missing values.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"other-modules-0-8-13","dir":"Changelog","previous_headings":"Enhancements","what":"Other modules","title":"teal.modules.clinical 0.8.13","text":"Updated tm_t_binary_outcome enable option apply continuity correction Newcombe method. Simplified show R code tm_g_pp_patient_timeline module. Improved names code chunks shown Debug Info. Improved validation treatment variable factor.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"bug-fixes-0-8-13","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.13","text":"Fixed summarize_logistic implementation broken empty string error. upstream. _NA_ new standard flag allow pivot empty entries data frames. Took @title tm_t_binary_outcome.R producing warning. Updated validation account error selecting single variable tm_g_pp_patient_timeline module.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-8-13","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.13","text":"Added pkgdown template documentation. Updated package authors.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-8-12","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.12","text":"Changed input Covariates tm_t_coxreg.R track user input reflect order table.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"new-features-0-8-12","dir":"Changelog","previous_headings":"","what":"New features","title":"teal.modules.clinical 0.8.12","text":"Added new module tm_t_shift_by_arm_by_worst analysis laboratory abnormalities severe grade flag. Enhanced tm_t_events_patyear include selected parameter title table. Enhanced tm_t_mult_events include selected parameter title table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"enhancements-0-8-12","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.12","text":"Rewrote modules use moduleServer updated calls teal.devel modules also written use moduleServer. Changed way obtaining selection ordered changes teal.devel. Use ordered = TRUE cs_to_des_select cs_to_select_spec return ordered selection. Replaced calls teal::root_modules teal::modules following deprecation teal::root_modules. tm_t_events_summary now allows nested arm_var columns matching outputs tm_t_events. Added validation tm_t_abnormality_by_worst_grade arm_var selected. Enhanced tm_t_binary_outcome include responders response table default. Added subtitle tm_g_forest_tte, tm_t_coxreg, tm_t_binary_outcome listing stratification factors.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"bug-fixes-0-8-12","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.12","text":"Fixed bug prevent processing empty sets data tm_g_forest_rsp.R causing shiny errors runtime. Fixed bug closed Compare Treatments conditional panel marked Combine comparison groups? option conflicted adding column patients tables tm_t_binary_outcome.R tm_t_tte.R.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-8-12-1","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.12","text":"Replaced deprecated rtables::var_labels calls documentation examples. Add import tern.mmrm package change references split tern. Adjusted package imports take account changes teal framework. Ensure consistent vertical order tm_g_pp_patient_timeline output switching absolute relative days.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"breaking-changes-0-8-11","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"teal.modules.clinical 0.8.11","text":"Updated tm_t_abnormality due changes count_abnormal abnormal argument taking list input now. Changed tm_g_pp_patient_timeline parameter, cmtrt, cmdecod.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"new-features-0-8-11","dir":"Changelog","previous_headings":"","what":"New features","title":"teal.modules.clinical 0.8.11","text":"Added new module tm_t_abnormality_by_worst_grade analysis laboratory test results highest grade post-baseline. Enhanced tm_t_ancova include selected parameter(s), visit(s) analysis variable title table. Added new module tm_g_lineplot creating line plots. Enhanced tm_t_logistic include selected parameter title table. Enhanced tm_g_forest_rsp include selected parameter title table. Enhanced tm_g_forest_tte include selected parameter title table. Enhanced tm_g_pp_patient_timeline bold axes labels integer values axis. Enhanced tm_g_ipp allow users display AVALU title y axis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"enhancements-0-8-11","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.11","text":"Added support logging logger package added info level logs upon initialization module. Added default_responses argument tm_t_binary_outcome tm_g_forest_rsp allow user specify default selected responses possible response levels. Updated tm_t_binary_outcome show selected responses output table selecting “Show Selected Response Categories”. Added rsp_table argument tm_t_binary_outcome allow user initialize module matching RSPT01 STREAM template. Added support custom arguments ggplot2::labs ggplot2::theme plot based modules. Added support custom arguments rtables::basic_table table based modules. Updated tm_t_binary_outcome enable option apply continuity correction Wilson method.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-8-11","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.11","text":"Updated required R version >= 3.6. Refactored calls defunct teal.devel::data_extract_input calls replacement teal.devel::data_extract_ui. Updated modules use new data_merge_module interface provided teal.devel removed usage now deprecated function teal.devel::get_input_order. Updated tm_t_binary_outcome module add template removed now deprecated module tm_t_rsp. Removed utils.nest dependency replaced calls checkmate equivalents.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"bug-fixes-0-8-11","dir":"Changelog","previous_headings":"","what":"Bug Fixes","title":"teal.modules.clinical 0.8.11","text":"Fixed bug tm_g_pp_therapy cmstdy cmendy argument type integer causes plot crash.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"new-features-0-8-10","dir":"Changelog","previous_headings":"","what":"New features","title":"teal.modules.clinical 0.8.10","text":"Added new module tm_t_smq analysis adverse events Standardized MedDRA Query. Added new module tm_t_shift_by_grade analysis grade laboratory abnormalities. Added new module tm_t_exposure analysis duration exposure risk management plan. Added new module tm_t_shift_by_arm can display shift table ECG interval data.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"bug-fixes-0-8-10","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.10","text":"Corrected tm_a_mmrm able consider treatment variable interactions. Fixed tm_t_binary_outcome tm_t_rsp choose correct CI estimation method Proportions Difference Stratified Analysis (.e. Wald-type confidence interval CMH weights).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"enhancements-0-8-10","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.10","text":"Added validation checks tm_t_rsp tm_t_binary_outcome stratification errors applied filters. Added tm_g_km validation check plot tables font size. Enhanced tm_g_km add selected paramcd plot title. tm_t_events now can display layouts two nested column treatment variables. options pruning sorting available. Exported package helper functions. Updated tm_t_events_by_grade display grading groups nested columns col_by_grade option support pruning sorting options like tm_t_events. Used format_count_fraction fix formatting inconsistency tm_t_events_summary. Updated count_occurrences vars argument tm_t_shift_by_grade. Updated tm_t_pp_laboratory display 4 decimals default. Updated tm_t_events_by_grade use trim_levels_in_group split function instead trim_rows function. Added table title tm_t_tte. Added table titles tm_t_rsp tm_t_binary_outcome.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-8-10","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.10","text":"Updated LICENCE README new package references. Added error_on_lint: TRUE .lintr. Removed insert_rrow updated usage count_patients_by_flags tm_t_events_summary. Changed package calls functions dplyr package. functions now fully specified (e.g. dplyr::filter).","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"new-features-0-8-9","dir":"Changelog","previous_headings":"","what":"New features","title":"teal.modules.clinical 0.8.9","text":"Added capability remember order user input encoding UI elements. Inputs marked double arrow icon tracking enabled. affected modules : tm_t_summary, tm_t_summary_by, tm_g_forest_rsp, tm_g_forest_tte, tm_t_events_summary, tm_t_abnormality, tm_t_mult_events. Added new argument numeric_stats tm_t_summary tm_t_summary_by control displayed summary statistics numeric variables. Added new argument drop_zero_levels tm_t_summary_by can drop rows zeros result table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"enhancements-0-8-9","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.9","text":"Split tm_g_patient_profile tabs 8 separate new modules. Added option select patient ID filter panel modules patient profile. Added validation tm_g_patient_timeline plot empty. Enhanced tm_a_mmrm work without treatment variable. Added option choose number decimal places rounding tm_t_pp_laboratory. Added check box tm_g_pp_patient_timeline hiding/showing relative study days x-axis. Added title patient’s id plots patient profile modules. Made gray error message tm_g_forest_tte informative deselecting Endpoint column left-hand encoding panel. Added twenty-fifth seventy-fifth quantile summary statistics tm_t_summary. Added interaction p-value column tm_t_coxreg. Added validation tm_t_ancova selected covariate variables contain one level. Added validation tm_t_events_patyear events variable empty. Changed font size input description tm_g_km precisely describe controls. Enhanced tm_t_logistic interaction choices depend selected covariates. Enhanced tm_t_rsp strata input visible comparing treatments.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"bug-fixes-0-8-9","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.9","text":"Fixed Get R Code output tm_t_pp_laboratory return identical HTML formatted table displayed app. Added validation tm_t_coxreg ensure treatment, strata covariate variables overlap. Limited label repel feature tm_g_pp_patient_timeline X-axis consistent look. Updated tm_t_summary_by paramcd required analyzing ADSL variables. Updated tm_t_coxreg can work covariate selected. Updated tm_a_mmrm can work treatment variable selected. Updated tm_g_forest_tte total number events also shown table. Updated tm_t_events_summary work pooled studies. Updated validation level tm_t_coxreg. Updated validation level tm_t_logistic. Added validation tm_t_binary_outcome tm_t_rsp ensure strata variable contains one level selecting one strata variable. Updated warning message deselecting statistics tm_t_summary tm_t_summary_by explain need select least one statistic.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"enhancements-0-8-8","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.8","text":"Added option download expand tables. tm_g_km added support downloading images updated x-axis label show title case. Added slider font size plots. Added persistence selected table lengths. timeline plot now supports edge cases. vitals tab, removed unused label text legend, updated plot display stable colors per levels, cleared x-axis limit fixed legend update filtering. Also added note clarify supported horizontal lines cases. Updated adverse events tab show warning message instead empty plot data empty. Fixed PARAMCD selected levels current patient. Updated pre-processing code inside template_tte dataset without events still produces table. Updated code use correct denominator duration response endpoints. Modified parameter arm_var accept one column. selecting two columns arm_var, second variable nest first one. Added argument show_labels template_summary show label single summary variable table. Added new parameter conf_arg tm_t_rsp consistent efficacy modules. Added validation statement tm_g_ipp module print message deselecting Timepoint Variable drop-. Removed header definition tm_g_forest_rsp tm_g_forest_tte now default header g_forest. Fixed validation statement tm_t_coxreg models without strata using likelihood tests return result. Clarified functionality drop_arm_levels tm_t_summary tm_t_summary_by. encodings panel, checkbox show parent dataset analysis dataset different.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-8-8","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.8","text":"Replaced remaining two observe function calls observeEvent optimize performance. Fixed grammar “Select patient’s id” error message tm_g_patient_profile. Fixed font_size default templates 12L instead vector 3 integers cleaned associated unnecessary code. Fixed deprecated function warning tm_g_barchart_simple. Fixed subgroup_var definition truncation tm_g_forest_rsp tm_g_forest_tte. Clarified labeling related regression type encoding panel tm_t_coxreg.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"bug-fixes-0-8-8","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.8","text":"Added validation case filtering rows therapy tab tm_g_patient_profile. Updated internals modules read data correct field filter_spec objects. Fixed reactivity filter panel PARAMCD variable levels input tm_g_patient_profile vitals tab plot get reset filtering. Updated vitals plot tab tm_g_patient_profile drop NA entries plot. Updated tm_t_coxreg take values account. Added check tm_t_coxreg interactions univariate models multivariate models. Updated tm_t_events_summary work pooled studies.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"new-module-0-8-7","dir":"Changelog","previous_headings":"","what":"New Module","title":"teal.modules.clinical 0.8.7","text":"Added new module tm_g_patient_profile profile patients based predefined categories. Added new module tm_g_ipp individual patient plots.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"enhancements-0-8-7","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.7","text":"Added argument drop_arm_levels safety modules. allows removal columns based factor levels found filtered data. Updated tm_g_km allow plot failure probability y-axis, tick interval selection x-axis option create plot without confidence interval ribbon (new default). Added argument time_unit_var template_g_km add time unit x-axis label.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-8-7","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.7","text":"Removed redundant Analysis Data: label Encodings Panel. Removed limit requiring 15 fewer columns tabulation modules. New upper threshold 100 columns. Decreased lower limit number observations required modules. Safety tables require least one record. Requirements efficacy outputs per treatment group: tm_a_mmrm requires five records, tm_t_logistic tm_t_coxreg require two records, remaining modules require least one record per treatment group. graphs, lower threshold two records. Removed argument cnsr_val tm_t_events_patyear added new argument events_var. arm_ref_comp_observer include parentname argument. Show R code include datasets retrieved data_extract_spec objects. Refactored stringr dependency patient profile module. Added missing table calls chunks tm_t_events tm_t_events_by_grade.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"new-features-0-8-6","dir":"Changelog","previous_headings":"","what":"New Features","title":"teal.modules.clinical 0.8.6","text":"Added new module tm_g_ci confidence interval plots. Added new module tm_t_ancova analysis variance summary tables. Added new module tm_t_mult_events multi-event tables.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"enhancements-0-8-6","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.6","text":"Refactored modules using redesigned rtables tern packages. Enhanced modules. now take advantage data_extract_spec data_merge_module functionality teal. Reduced clutter repeated datasets encodings panels. Updated modules use OptionalSelectInput conf_level.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"miscellaneous-0-8-6","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.6","text":"Added vignette substitute can helpful developing analysis template functions teal modules.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"bug-fixes-0-8-6","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.6","text":"Updated tm_t_events module use user’s non-default choices prune_freq prune_diff.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"tealmodulesclinical-085","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.8.5","title":"teal.modules.clinical 0.8.5","text":"graph modules now accept plot_width argument specifies plot width renders slider adjust width interactively module. FilteredData object now passed arm_ref_comp_observer modules now support nested lists containing delayed_data objects. Replace plot_with_height module new plot_with_settings module. Update examples use code argument inside cdisc_dataset.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"tealmodulesclinical-084","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.8.4","title":"teal.modules.clinical 0.8.4","text":"Extend tm_t_coxreg optionally produce univariate Cox regressions. Updated tm_t_binary_outcome display Odds Ratio estimates, include new methods CIs p-values display summary individual response categories. Updated tm_t_tte optionally compare arms, removed conf_level argument. Updated tm_g_km optionally compare arms. Extend tm_g_km optionally scale X axis range case one plot. New tm_a_mmrm MMRM analysis. Deprecated tm_t_mmrm (superseded tm_a_mmrm).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"tealmodulesclinical-083","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.8.3","title":"teal.modules.clinical 0.8.3","text":"New tm_t_coxreg module multi-variable Cox regressions. New tm_t_binary_outcome module. New tm_t_events_patyear module: events rate adjusted patient-year risk table. Remove grade_levels argument tm_t_events_by_grade. Updated response table single arm. New tm_t_abnormality module. Removed get_relabel_call get_relabel_call2 favor teal.devel::get_relabel_call teal.devel::get_anl_relabel_call.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"tealmodulesclinical-082","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.8.2","title":"teal.modules.clinical 0.8.2","text":"Add confidence level survfit, coxph, ztest; add confidence type, ties, percentiles tm_t_tte. Optionally use single term tm_t_events tm_t_events_by_grade modules. New tm_t_logistic module. New tm_t_mmrm module. New modules tm_t_summary_by tm_t_events_summary. Add stratified analysis tm_g_forest_tte tm_g_forest_rsp. Add confidence level plotting symbol size options tm_g_forest_rsp tm_g_forest_tte.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"tealmodulesclinical-081","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.8.1","title":"teal.modules.clinical 0.8.1","text":"New tm_t_events tm_t_events_by_grade modules.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"tealmodulesclinical-080","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.8.0","title":"teal.modules.clinical 0.8.0","text":"Optionally show KM CoxPH table tm_g_km.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"tealmodulesclinical-070","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.7.0","title":"teal.modules.clinical 0.7.0","text":"Use teal.devel.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/news/index.html","id":"tealmodulesclinical-060","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.6.0","title":"teal.modules.clinical 0.6.0","text":"Package renamed teal.modules.clinical. Rename tm_t_summarize_variables tm_t_summary. Usage teal::choices_selected() function instead *_var *_var_choices arguments.","code":""}]
+[{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CODE_OF_CONDUCT.html","id":"our-pledge","dir":"","previous_headings":"","what":"Our Pledge","title":"Contributor Covenant Code of Conduct","text":"members, contributors, leaders pledge make participation community harassment-free experience everyone, regardless age, body size, visible invisible disability, ethnicity, sex characteristics, gender identity expression, level experience, education, socio-economic status, nationality, personal appearance, race, caste, color, religion, sexual identity orientation. pledge act interact ways contribute open, welcoming, diverse, inclusive, healthy community.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CODE_OF_CONDUCT.html","id":"our-standards","dir":"","previous_headings":"","what":"Our Standards","title":"Contributor Covenant Code of Conduct","text":"Examples behavior contributes positive environment community include: Demonstrating empathy kindness toward people respectful differing opinions, viewpoints, experiences Giving gracefully accepting constructive feedback Accepting responsibility apologizing affected mistakes, learning experience Focusing best just us individuals, overall community Examples unacceptable behavior include: use sexualized language imagery, sexual attention advances kind Trolling, insulting derogatory comments, personal political attacks Public private harassment Publishing others’ private information, physical email address, without explicit permission conduct reasonably considered inappropriate professional setting","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CODE_OF_CONDUCT.html","id":"enforcement-responsibilities","dir":"","previous_headings":"","what":"Enforcement Responsibilities","title":"Contributor Covenant Code of Conduct","text":"Community leaders responsible clarifying enforcing standards acceptable behavior take appropriate fair corrective action response behavior deem inappropriate, threatening, offensive, harmful. Community leaders right responsibility remove, edit, reject comments, commits, code, wiki edits, issues, contributions aligned Code Conduct, communicate reasons moderation decisions appropriate.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CODE_OF_CONDUCT.html","id":"scope","dir":"","previous_headings":"","what":"Scope","title":"Contributor Covenant Code of Conduct","text":"Code Conduct applies within community spaces, also applies individual officially representing community public spaces. Examples representing community include using official e-mail address, posting via official social media account, acting appointed representative online offline event.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CODE_OF_CONDUCT.html","id":"enforcement","dir":"","previous_headings":"","what":"Enforcement","title":"Contributor Covenant Code of Conduct","text":"Instances abusive, harassing, otherwise unacceptable behavior may reported community leaders responsible enforcement [INSERT CONTACT METHOD]. complaints reviewed investigated promptly fairly. community leaders obligated respect privacy security reporter incident.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CODE_OF_CONDUCT.html","id":"enforcement-guidelines","dir":"","previous_headings":"","what":"Enforcement Guidelines","title":"Contributor Covenant Code of Conduct","text":"Community leaders follow Community Impact Guidelines determining consequences action deem violation Code Conduct:","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CODE_OF_CONDUCT.html","id":"id_1-correction","dir":"","previous_headings":"Enforcement Guidelines","what":"1. Correction","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Use inappropriate language behavior deemed unprofessional unwelcome community. Consequence: private, written warning community leaders, providing clarity around nature violation explanation behavior inappropriate. public apology may requested.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CODE_OF_CONDUCT.html","id":"id_2-warning","dir":"","previous_headings":"Enforcement Guidelines","what":"2. Warning","title":"Contributor Covenant Code of Conduct","text":"Community Impact: violation single incident series actions. Consequence: warning consequences continued behavior. interaction people involved, including unsolicited interaction enforcing Code Conduct, specified period time. includes avoiding interactions community spaces well external channels like social media. Violating terms may lead temporary permanent ban.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CODE_OF_CONDUCT.html","id":"id_3-temporary-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"3. Temporary Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: serious violation community standards, including sustained inappropriate behavior. Consequence: temporary ban sort interaction public communication community specified period time. public private interaction people involved, including unsolicited interaction enforcing Code Conduct, allowed period. Violating terms may lead permanent ban.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CODE_OF_CONDUCT.html","id":"id_4-permanent-ban","dir":"","previous_headings":"Enforcement Guidelines","what":"4. Permanent Ban","title":"Contributor Covenant Code of Conduct","text":"Community Impact: Demonstrating pattern violation community standards, including sustained inappropriate behavior, harassment individual, aggression toward disparagement classes individuals. Consequence: permanent ban sort public interaction within community.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CODE_OF_CONDUCT.html","id":"attribution","dir":"","previous_headings":"","what":"Attribution","title":"Contributor Covenant Code of Conduct","text":"Code Conduct adapted Contributor Covenant, version 2.1, available https://www.contributor-covenant.org/version/2/1/code_of_conduct.html. Community Impact Guidelines inspired Mozilla’s code conduct enforcement ladder. answers common questions code conduct, see FAQ https://www.contributor-covenant.org/faq. Translations available https://www.contributor-covenant.org/translations.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":null,"dir":"","previous_headings":"","what":"Contribution Guidelines","title":"Contribution Guidelines","text":"🙏 Thank taking time contribute! input deeply valued, whether issue, pull request, even feedback, regardless size, content scope.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"table-of-contents","dir":"","previous_headings":"","what":"Table of contents","title":"Contribution Guidelines","text":"👶 Getting started 📔 Code Conduct 🗃 License 📜 Issues 🚩 Pull requests 💻 Coding guidelines 🏆 Recognition model ❓ Questions","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"getting-started","dir":"","previous_headings":"","what":"Getting started","title":"Contribution Guidelines","text":"Please refer project documentation brief introduction. Please also see articles within project documentation additional information.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"code-of-conduct","dir":"","previous_headings":"","what":"Code of Conduct","title":"Contribution Guidelines","text":"Code Conduct governs project. Participants contributors expected follow rules outlined therein.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"license","dir":"","previous_headings":"","what":"License","title":"Contribution Guidelines","text":"contributions covered project’s license.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"issues","dir":"","previous_headings":"","what":"Issues","title":"Contribution Guidelines","text":"use GitHub track issues, feature requests, bugs. submitting new issue, please check issue already reported. issue already exists, please upvote existing issue 👍. new feature requests, please elaborate context benefit feature users, developers, relevant personas.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"github-flow","dir":"","previous_headings":"Pull requests","what":"GitHub Flow","title":"Contribution Guidelines","text":"repository uses GitHub Flow model collaboration. submit pull request: Create branch Please see branch naming convention . don’t write access repository, please fork . Make changes Make sure code passes checks imposed GitHub Actions well documented well tested unit tests sufficiently covering changes introduced Create pull request (PR) pull request description, please link relevant issue (), provide detailed description change, include assumptions. Address review comments, Post approval Merge PR write access. Otherwise, reviewer merge PR behalf. Pat back Congratulations! 🎉 now official contributor project! grateful contribution.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"branch-naming-convention","dir":"","previous_headings":"Pull requests","what":"Branch naming convention","title":"Contribution Guidelines","text":"Suppose changes related current issue current project; please name branch follows: _. Please use underscore (_) delimiter word separation. example, 420_fix_ui_bug suitable branch name change resolving UI-related bug reported issue number 420 current project. change affects multiple repositories, please name branches follows: __. example, 69_awesomeproject_fix_spelling_error reference issue 69 reported project awesomeproject aims resolve one spelling errors multiple (likely related) repositories.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"monorepo-and-stageddependencies","dir":"","previous_headings":"Pull requests","what":"monorepo and staged.dependencies","title":"Contribution Guidelines","text":"Sometimes might need change upstream dependent package(s) able submit meaningful change. using staged.dependencies functionality simulate monorepo behavior. dependency configuration already specified project’s staged_dependencies.yaml file. need name feature branches appropriately. exception branch naming convention described . Please refer staged.dependencies package documentation details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"coding-guidelines","dir":"","previous_headings":"","what":"Coding guidelines","title":"Contribution Guidelines","text":"repository follows unified processes standards adopted maintainers ensure software development carried consistently within teams cohesively across repositories.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"style-guide","dir":"","previous_headings":"Coding guidelines","what":"Style guide","title":"Contribution Guidelines","text":"repository follows standard tidyverse style guide uses lintr lint checks. Customized lint configurations available repository’s .lintr file.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"dependency-management","dir":"","previous_headings":"Coding guidelines","what":"Dependency management","title":"Contribution Guidelines","text":"Lightweight right weight. repository follows tinyverse recommedations limiting dependencies minimum.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"dependency-version-management","dir":"","previous_headings":"Coding guidelines","what":"Dependency version management","title":"Contribution Guidelines","text":"code compatible (!) historical versions given dependenct package, required specify minimal version DESCRIPTION file. particular: development version requires (imports) development version another package - required put abc (>= 1.2.3.9000).","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"r--package-versions","dir":"","previous_headings":"Coding guidelines > Recommended development environment & tools","what":"R & package versions","title":"Contribution Guidelines","text":"continuously test packages newest R version along recent dependencies CRAN BioConductor. recommend working environment also set way. can find details R version packages used R CMD check GitHub Action execution log - step prints R sessionInfo(). discover bugs older R versions older set dependencies, please create relevant bug reports.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"pre-commit","dir":"","previous_headings":"Coding guidelines > Recommended development environment & tools","what":"pre-commit","title":"Contribution Guidelines","text":"highly recommend use pre-commit tool combined R hooks pre-commit execute checks committing pushing changes. Pre-commit hooks already available repository’s .pre-commit-config.yaml file.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"recognition-model","dir":"","previous_headings":"","what":"Recognition model","title":"Contribution Guidelines","text":"mentioned previously, contributions deeply valued appreciated. contribution data available part repository insights, recognize significant contribution hence add contributor package authors list, following rules enforced: Minimum 5% lines code authored* (determined git blame query) top 5 contributors terms number commits lines added lines removed* *Excluding auto-generated code, including limited roxygen comments renv.lock files. package maintainer also reserves right adjust criteria recognize contributions.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/CONTRIBUTING.html","id":"questions","dir":"","previous_headings":"","what":"Questions","title":"Contribution Guidelines","text":"questions regarding contribution guidelines, please contact package/repository maintainer.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/SECURITY.html","id":"reporting-security-issues","dir":"","previous_headings":"","what":"Reporting Security Issues","title":"Security Policy","text":"believe found security vulnerability repositories organization, please report us coordinated disclosure. Please report security vulnerabilities public GitHub issues, discussions, pull requests. Instead, please send email vulnerability.management[@]roche.com. Please include much information listed can help us better understand resolve issue: type issue (e.g., buffer overflow, SQL injection, cross-site scripting) Full paths source file(s) related manifestation issue location affected source code (tag/branch/commit direct URL) special configuration required reproduce issue Step--step instructions reproduce issue Proof--concept exploit code (possible) Impact issue, including attacker might exploit issue information help us triage report quickly.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/SECURITY.html","id":"data-security-standards-dss","dir":"","previous_headings":"","what":"Data Security Standards (DSS)","title":"Security Policy","text":"Please make sure reporting issues form bug, feature, pull request, sensitive information PII, PHI, PCI completely removed text attachments, including pictures videos.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"generating-minimal-data-to-test-teal-modules-clinical","dir":"Articles","previous_headings":"","what":"Generating minimal data to test teal.modules.clinical","title":"Example Data Generation","text":"following script used create save cached synthetic CDISC data data/ directory use examples tests teal.modules.clinical package. script/vignette initialized Emily de la Rua tern. Disclaimer: vignette concerns mainly development minimal stable test data kept internal feature tracking.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"setup-helper-functions","dir":"Articles","previous_headings":"","what":"Setup & Helper Functions","title":"Example Data Generation","text":"","code":"library(dplyr) library(teal.data) study_duration_secs <- lubridate::seconds(lubridate::years(2)) sample_fct <- function(x, N, ...) { checkmate::assert_number(N) factor(sample(x, N, replace = TRUE, ...), levels = if (is.factor(x)) levels(x) else x) } retain <- function(df, value_var, event, outside = NA) { indices <- c(1, which(event == TRUE), nrow(df) + 1) values <- c(outside, value_var[event == TRUE]) rep(values, diff(indices)) } relvar_init <- function(relvar1, relvar2) { if (length(relvar1) != length(relvar2)) { message(simpleError( \"The argument value length of relvar1 and relvar2 differ. They must contain the same number of elements.\" )) return(NA) } return(list(\"relvar1\" = relvar1, \"relvar2\" = relvar2)) } rel_var <- function(df = NULL, var_name = NULL, var_values = NULL, related_var = NULL) { if (is.null(df)) { message(\"Missing data frame argument value.\") return(NA) } else { n_relvar1 <- length(unique(df[, related_var, drop = TRUE])) n_relvar2 <- length(var_values) if (n_relvar1 != n_relvar2) { message(paste(\"Unequal vector lengths for\", related_var, \"and\", var_name)) return(NA) } else { relvar1 <- unique(df[, related_var, drop = TRUE]) relvar2_values <- rep(NA, nrow(df)) for (r in seq_len(length(relvar1))) { matched <- which(df[, related_var, drop = TRUE] == relvar1[r]) relvar2_values[matched] <- var_values[r] } return(relvar2_values) } } } visit_schedule <- function(visit_format = \"WEEK\", n_assessments = 10L, n_days = 5L) { if (!(toupper(visit_format) %in% c(\"WEEK\", \"CYCLE\"))) { message(\"Visit format value must either be: WEEK or CYCLE\") return(NA) } if (toupper(visit_format) == \"WEEK\") { assessments <- 1:n_assessments assessments_ord <- -1:n_assessments visit_values <- c(\"SCREENING\", \"BASELINE\", paste(toupper(visit_format), assessments, \"DAY\", (assessments * 7) + 1)) } else if (toupper(visit_format) == \"CYCLE\") { cycles <- sort(rep(1:n_assessments, times = 1, each = n_days)) days <- rep(seq(1:n_days), times = n_assessments, each = 1) assessments_ord <- 0:(n_assessments * n_days) visit_values <- c(\"SCREENING\", paste(toupper(visit_format), cycles, \"DAY\", days)) } visit_values <- stats::reorder(factor(visit_values), assessments_ord) } rtpois <- function(n, lambda) stats::qpois(stats::runif(n, stats::dpois(0, lambda), 1), lambda) rtexp <- function(n, rate, l = NULL, r = NULL) { if (!is.null(l)) { l - log(1 - stats::runif(n)) / rate } else if (!is.null(r)) { -log(1 - stats::runif(n) * (1 - exp(-r * rate))) / rate } else { stats::rexp(n, rate) } } str_extract <- function(string, pattern) regmatches(string, gregexpr(pattern, string)) with_label <- function(x, label) { attr(x, \"label\") <- as.vector(label) x } common_var_labels <- c( USUBJID = \"Unique Subject Identifier\", STUDYID = \"Study Identifier\", PARAM = \"Parameter\", PARAMCD = \"Parameter Code\", AVISIT = \"Analysis Visit\", AVISITN = \"Analysis Visit (N)\", AVAL = \"Analysis Value\", AVALU = \"Analysis Value Unit\", AVALC = \"Character Result/Finding\", BASE = \"Baseline Value\", BASE2 = \"Screening Value\", ABLFL = \"Baseline Record Flag\", ABLFL2 = \"Screening Record Flag\", CHG = \"Absolute Change from Baseline\", PCHG = \"Percentage Change from Baseline\", ANRIND = \"Analysis Reference Range Indicator\", BNRIND = \"Baseline Reference Range Indicator\", ANRLO = \"Analysis Normal Range Lower Limit\", ANRHI = \"Analysis Normal Range Upper Limit\", CNSR = \"Censor\", ADTM = \"Analysis Datetime\", ADY = \"Analysis Relative Day\", ASTDY = \"Analysis Start Relative Day\", AENDY = \"Analysis End Relative Day\", ASTDTM = \"Analysis Start Datetime\", AENDTM = \"Analysis End Datetime\", VISITDY = \"Planned Study Day of Visit\", EVNTDESC = \"Event or Censoring Description\", CNSDTDSC = \"Censor Date Description\", BASETYPE = \"Baseline Type\", DTYPE = \"Derivation Type\", ONTRTFL = \"On Treatment Record Flag\", WORS01FL = \"Worst Observation in Window Flag 01\", WORS02FL = \"Worst Post-Baseline Observation\" )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"adsl","dir":"Articles","previous_headings":"","what":"ADSL","title":"Example Data Generation","text":"","code":"generate_adsl <- function(N = 200) { set.seed(1) sys_dtm <- lubridate::fast_strptime(\"20/2/2019 11:16:16.683\", \"%d/%m/%Y %H:%M:%OS\", tz = \"UTC\") country_site_prob <- c(.5, .121, .077, .077, .075, .052, .046, .025, .014, .003) adsl <- tibble::tibble( STUDYID = rep(\"AB12345\", N) %>% with_label(\"Study Identifier\"), COUNTRY = sample_fct( c(\"CHN\", \"USA\", \"BRA\", \"PAK\", \"NGA\", \"RUS\", \"JPN\", \"GBR\", \"CAN\", \"CHE\"), N, prob = country_site_prob ) %>% with_label(\"Country\"), SITEID = sample_fct(1:20, N, prob = rep(country_site_prob, times = 2)), SUBJID = paste(\"id\", seq_len(N), sep = \"-\") %>% with_label(\"Subject Identifier for the Study\"), AGE = (sapply(stats::rchisq(N, df = 5, ncp = 10), max, 0) + 20) %>% with_label(\"Age\"), SEX = c(\"F\", \"M\") %>% sample_fct(N, prob = c(.52, .48)) %>% with_label(\"Sex\"), ARMCD = c(\"ARM A\", \"ARM B\", \"ARM C\") %>% sample_fct(N) %>% with_label(\"Planned Arm Code\"), ARM = dplyr::recode( .data$ARMCD, \"ARM A\" = \"A: Drug X\", \"ARM B\" = \"B: Placebo\", \"ARM C\" = \"C: Combination\" ) %>% with_label(\"Description of Planned Arm\"), ACTARMCD = .data$ARMCD %>% with_label(\"Actual Arm Code\"), ACTARM = .data$ARM %>% with_label(\"Description of Actual Arm\"), RACE = c( \"ASIAN\", \"BLACK OR AFRICAN AMERICAN\", \"WHITE\", \"AMERICAN INDIAN OR ALASKA NATIVE\", \"MULTIPLE\", \"NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER\", \"OTHER\", \"UNKNOWN\" ) %>% sample_fct(N, prob = c(.55, .23, .16, .05, .004, .003, .002, .002)) %>% with_label(\"Race\"), TRTSDTM = sys_dtm + sample(seq(0, study_duration_secs), size = N, replace = TRUE) %>% with_label(\"Datetime of First Exposure to Treatment\"), TRTEDTM = c(TRTSDTM + study_duration_secs) %>% with_label(\"Datetime of Last Exposure to Treatment\"), EOSDY = ceiling(as.numeric(difftime(TRTEDTM, TRTSDTM, units = \"days\"))) %>% with_label(\"End of Study Relative Day\"), EOSDT = lubridate::date(TRTEDTM) %>% with_label(\"End of Study Date\"), STRATA1 = c(\"A\", \"B\", \"C\") %>% sample_fct(N) %>% with_label(\"Stratification Factor 1\"), STRATA2 = c(\"S1\", \"S2\") %>% sample_fct(N) %>% with_label(\"Stratification Factor 2\"), BMRKR1 = stats::rchisq(N, 6) %>% with_label(\"Continuous Level Biomarker 1\"), BMRKR2 = sample_fct(c(\"LOW\", \"MEDIUM\", \"HIGH\"), N) %>% with_label(\"Continuous Level Biomarker 2\") ) # associate sites with countries and regions adsl <- adsl %>% dplyr::mutate( SITEID = paste0(.data$COUNTRY, \"-\", .data$SITEID) %>% with_label(\"Study Site Identifier\"), REGION1 = factor(dplyr::case_when( COUNTRY %in% c(\"NGA\") ~ \"Africa\", COUNTRY %in% c(\"CHN\", \"JPN\", \"PAK\") ~ \"Asia\", COUNTRY %in% c(\"RUS\") ~ \"Eurasia\", COUNTRY %in% c(\"GBR\") ~ \"Europe\", COUNTRY %in% c(\"CAN\", \"USA\") ~ \"North America\", COUNTRY %in% c(\"BRA\") ~ \"South America\", TRUE ~ as.character(NA) )) %>% with_label(\"Geographic Region 1\"), SAFFL = factor(\"Y\") %>% with_label(\"Safety Population Flag\") ) %>% dplyr::mutate( USUBJID = paste(.data$STUDYID, .data$SITEID, .data$SUBJID, sep = \"-\") %>% with_label(\"Unique Subject Identifier\") ) # disposition related variables # using probability of 1 for the \"DEATH\" level to ensure at least one death record exists l_dcsreas <- list( choices = c( \"ADVERSE EVENT\", \"DEATH\", \"LACK OF EFFICACY\", \"PHYSICIAN DECISION\", \"PROTOCOL VIOLATION\", \"WITHDRAWAL BY PARENT/GUARDIAN\", \"WITHDRAWAL BY SUBJECT\" ), prob = c(.2, 1, .1, .1, .2, .1, .1) ) l_dthcat_other <- list( choices = c( \"Post-study reporting of death\", \"LOST TO FOLLOW UP\", \"MISSING\", \"SUICIDE\", \"UNKNOWN\" ), prob = c(.1, .3, .3, .2, .1) ) adsl <- adsl %>% dplyr::mutate( EOSSTT = dplyr::case_when( EOSDY == max(EOSDY, na.rm = TRUE) ~ \"COMPLETED\", EOSDY < max(EOSDY, na.rm = TRUE) ~ \"DISCONTINUED\", is.na(TRTEDTM) ~ \"ONGOING\" ) %>% with_label(\"End of Study Status\") ) %>% dplyr::mutate( EOTSTT = .data$EOSSTT %>% with_label(\"End of Treatment Status\") ) %>% dplyr::mutate( DCSREAS = ifelse( .data$EOSSTT == \"DISCONTINUED\", sample(x = l_dcsreas$choices, size = N, replace = TRUE, prob = l_dcsreas$prob), as.character(NA) ) %>% with_label(\"Reason for Discontinuation from Study\") ) tmc_ex_adsl <- adsl %>% dplyr::mutate(DTHDT = dplyr::case_when( DCSREAS == \"DEATH\" ~ lubridate::date(TRTEDTM + lubridate::days(sample(0:50, size = N, replace = TRUE))) ) %>% with_label(\"Date of Death\")) save(tmc_ex_adsl, file = \"data/tmc_ex_adsl.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"adae","dir":"Articles","previous_headings":"","what":"ADAE","title":"Example Data Generation","text":"","code":"generate_adae <- function(adsl = tmc_ex_adsl, max_n_aes = 5) { set.seed(1) lookup_ae <- tibble::tribble( ~AEBODSYS, ~AELLT, ~AEDECOD, ~AEHLT, ~AEHLGT, ~AETOXGR, ~AESOC, ~AESER, ~AEREL, \"cl A.1\", \"llt A.1.1.1.1\", \"dcd A.1.1.1.1\", \"hlt A.1.1.1\", \"hlgt A.1.1\", \"1\", \"cl A\", \"N\", \"N\", \"cl A.1\", \"llt A.1.1.1.2\", \"dcd A.1.1.1.2\", \"hlt A.1.1.1\", \"hlgt A.1.1\", \"2\", \"cl A\", \"Y\", \"N\", \"cl B.1\", \"llt B.1.1.1.1\", \"dcd B.1.1.1.1\", \"hlt B.1.1.1\", \"hlgt B.1.1\", \"5\", \"cl B\", \"Y\", \"Y\", \"cl B.2\", \"llt B.2.1.2.1\", \"dcd B.2.1.2.1\", \"hlt B.2.1.2\", \"hlgt B.2.1\", \"3\", \"cl B\", \"N\", \"N\", \"cl B.2\", \"llt B.2.2.3.1\", \"dcd B.2.2.3.1\", \"hlt B.2.2.3\", \"hlgt B.2.2\", \"1\", \"cl B\", \"Y\", \"N\", \"cl C.1\", \"llt C.1.1.1.3\", \"dcd C.1.1.1.3\", \"hlt C.1.1.1\", \"hlgt C.1.1\", \"4\", \"cl C\", \"N\", \"Y\", \"cl C.2\", \"llt C.2.1.2.1\", \"dcd C.2.1.2.1\", \"hlt C.2.1.2\", \"hlgt C.2.1\", \"2\", \"cl C\", \"N\", \"Y\", \"cl D.1\", \"llt D.1.1.1.1\", \"dcd D.1.1.1.1\", \"hlt D.1.1.1\", \"hlgt D.1.1\", \"5\", \"cl D\", \"Y\", \"Y\", \"cl D.1\", \"llt D.1.1.4.2\", \"dcd D.1.1.4.2\", \"hlt D.1.1.4\", \"hlgt D.1.1\", \"3\", \"cl D\", \"N\", \"N\", \"cl D.2\", \"llt D.2.1.5.3\", \"dcd D.2.1.5.3\", \"hlt D.2.1.5\", \"hlgt D.2.1\", \"1\", \"cl D\", \"N\", \"Y\" ) aag <- utils::read.table( sep = \",\", header = TRUE, text = paste( \"NAMVAR,SRCVAR,GRPTYPE,REFNAME,REFTERM,SCOPE\", \"CQ01NAM,AEDECOD,CUSTOM,D.2.1.5.3/A.1.1.1.1 aesi,dcd D.2.1.5.3,\", \"CQ01NAM,AEDECOD,CUSTOM,D.2.1.5.3/A.1.1.1.1 aesi,dcd A.1.1.1.1,\", \"SMQ01NAM,AEDECOD,SMQ,C.1.1.1.3/B.2.2.3.1 aesi,dcd C.1.1.1.3,BROAD\", \"SMQ01NAM,AEDECOD,SMQ,C.1.1.1.3/B.2.2.3.1 aesi,dcd B.2.2.3.1,BROAD\", \"SMQ02NAM,AEDECOD,SMQ,Y.9.9.9.9/Z.9.9.9.9 aesi,dcd Y.9.9.9.9,NARROW\", \"SMQ02NAM,AEDECOD,SMQ,Y.9.9.9.9/Z.9.9.9.9 aesi,dcd Z.9.9.9.9,NARROW\", sep = \"\\n\" ), stringsAsFactors = FALSE ) adae <- Map( function(id, sid) { n_aes <- sample(c(0, seq_len(max_n_aes)), 1) i <- sample(seq_len(nrow(lookup_ae)), n_aes, TRUE) dplyr::mutate( lookup_ae[i, ], USUBJID = id, STUDYID = sid ) }, adsl$USUBJID, adsl$STUDYID ) %>% Reduce(rbind, .) %>% `[`(c(10, 11, 1, 2, 3, 4, 5, 6, 7, 8, 9)) %>% dplyr::mutate( AETERM = gsub(\"dcd\", \"trm\", .data$AEDECOD) %>% with_label(\"Reported Term for the Adverse Event\"), AESEV = dplyr::case_when( AETOXGR == 1 ~ \"MILD\", AETOXGR %in% c(2, 3) ~ \"MODERATE\", AETOXGR %in% c(4, 5) ~ \"SEVERE\" ) %>% with_label(\"Severity/Intensity\") ) # merge adsl to be able to add AE date and study day variables adae <- dplyr::inner_join(adae, adsl, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\") %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::mutate(ASTDTM = sample( seq(lubridate::as_datetime(TRTSDTM), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1 )) %>% dplyr::mutate(ASTDY = ceiling(difftime(ASTDTM, TRTSDTM, units = \"days\"))) %>% # add 1 to end of range incase both values passed to sample() are the same dplyr::mutate(AENDTM = sample( seq(lubridate::as_datetime(ASTDTM), lubridate::as_datetime(TRTENDT + 1), by = \"day\"), size = 1 )) %>% dplyr::mutate(AENDY = ceiling(difftime(AENDTM, TRTSDTM, units = \"days\"))) %>% dplyr::mutate(LDOSEDTM = dplyr::case_when( TRTSDTM < ASTDTM ~ lubridate::as_datetime(stats::runif(1, TRTSDTM, ASTDTM)), TRUE ~ ASTDTM )) %>% dplyr::select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ASTDTM, .data$AETERM) adae <- adae %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(AESEQ = seq_len(dplyr::n())) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$ASTDTM, .data$AETERM, .data$AESEQ ) outcomes <- c( \"UNKNOWN\", \"NOT RECOVERED/NOT RESOLVED\", \"RECOVERED/RESOLVED WITH SEQUELAE\", \"RECOVERING/RESOLVING\", \"RECOVERED/RESOLVED\" ) adae <- adae %>% dplyr::mutate( AEOUT = factor(ifelse( .data$AETOXGR == \"5\", \"FATAL\", as.character(sample_fct(outcomes, nrow(adae), prob = c(0.1, 0.2, 0.1, 0.3, 0.3))) )) %>% with_label(\"Outcome of Adverse Event\"), TRTEMFL = ifelse(.data$ASTDTM >= .data$TRTSDTM, \"Y\", \"\") %>% with_label(\"Treatment Emergent Analysis Flag\") ) l_aag <- split(aag, interaction(aag$NAMVAR, aag$SRCVAR, aag$GRPTYPE, drop = TRUE)) # Create aesi flags l_aesi <- lapply(l_aag, function(d_adag, d_adae) { names(d_adag)[names(d_adag) == \"REFTERM\"] <- d_adag$SRCVAR[1] names(d_adag)[names(d_adag) == \"REFNAME\"] <- d_adag$NAMVAR[1] if (d_adag$GRPTYPE[1] == \"CUSTOM\") { d_adag <- d_adag[-which(names(d_adag) == \"SCOPE\")] } else if (d_adag$GRPTYPE[1] == \"SMQ\") { names(d_adag)[names(d_adag) == \"SCOPE\"] <- paste0(substr(d_adag$NAMVAR[1], 1, 5), \"SC\") } d_adag <- d_adag[-which(names(d_adag) %in% c(\"NAMVAR\", \"SRCVAR\", \"GRPTYPE\"))] d_new <- dplyr::left_join(x = d_adae, y = d_adag, by = intersect(names(d_adae), names(d_adag))) d_new[, dplyr::setdiff(names(d_new), names(d_adae)), drop = FALSE] }, adae) adae <- dplyr::bind_cols(adae, l_aesi) actions <- c( \"DOSE RATE REDUCED\", \"UNKNOWN\", \"NOT APPLICABLE\", \"DRUG INTERRUPTED\", \"DRUG WITHDRAWN\", \"DOSE INCREASED\", \"DOSE NOT CHANGED\", \"DOSE REDUCED\", \"NOT EVALUABLE\" ) tmc_ex_adae <- adae %>% dplyr::mutate( AEACN = factor(ifelse( .data$AETOXGR == \"5\", \"NOT EVALUABLE\", as.character(sample_fct(actions, nrow(adae), prob = c(0.05, 0.05, 0.05, 0.01, 0.05, 0.1, 0.45, 0.1, 0.05))) )) %>% with_label(\"Action Taken With Study Treatment\") ) %>% col_relabel( AEBODSYS = \"Body System or Organ Class\", AELLT = \"Lowest Level Term\", AEDECOD = \"Dictionary-Derived Term\", AEHLT = \"High Level Term\", AEHLGT = \"High Level Group Term\", AETOXGR = \"Analysis Toxicity Grade\", AESOC = \"Primary System Organ Class\", AESER = \"Serious Event\", AEREL = \"Analysis Causality\", AESEQ = \"Sponsor-Defined Identifier\", LDOSEDTM = \"End Time/Time of Last Dose\", CQ01NAM = \"CQ 01 Reference Name\", SMQ01NAM = \"SMQ 01 Reference Name\", SMQ01SC = \"SMQ 01 Scope\", SMQ02NAM = \"SMQ 02 Reference Name\", SMQ02SC = \"SMQ 02 Scope\" ) i_lbls <- sapply( names(col_labels(tmc_ex_adae)[is.na(col_labels(tmc_ex_adae))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adae[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adae, file = \"data/tmc_ex_adae.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"adaette","dir":"Articles","previous_headings":"","what":"ADAETTE","title":"Example Data Generation","text":"","code":"generate_adaette <- function(adsl = tmc_ex_adsl) { set.seed(1) lookup_adaette <- tibble::tribble( ~ARM, ~CATCD, ~CAT, ~LAMBDA, ~CNSR_P, \"ARM A\", \"1\", \"any adverse event\", 1 / 80, 0.4, \"ARM B\", \"1\", \"any adverse event\", 1 / 100, 0.2, \"ARM C\", \"1\", \"any adverse event\", 1 / 60, 0.42, \"ARM A\", \"2\", \"any serious adverse event\", 1 / 100, 0.3, \"ARM B\", \"2\", \"any serious adverse event\", 1 / 150, 0.1, \"ARM C\", \"2\", \"any serious adverse event\", 1 / 80, 0.32, \"ARM A\", \"3\", \"a grade 3-5 adverse event\", 1 / 80, 0.2, \"ARM B\", \"3\", \"a grade 3-5 adverse event\", 1 / 100, 0.08, \"ARM C\", \"3\", \"a grade 3-5 adverse event\", 1 / 60, 0.23 ) evntdescr_sel <- \"Preferred Term\" cnsdtdscr_sel <- c( \"Clinical Cut Off\", \"Completion or Discontinuation\", \"End of AE Reporting Period\" ) random_patient_data <- function(patient_info) { startdt <- lubridate::date(patient_info$TRTSDTM) trtedtm <- lubridate::floor_date(dplyr::case_when( is.na(patient_info$TRTEDTM) ~ lubridate::date(patient_info$TRTSDTM) + study_duration_secs, TRUE ~ lubridate::date(patient_info$TRTEDTM) ), unit = \"day\") enddts <- c(patient_info$EOSDT, lubridate::date(trtedtm)) enddts_min_index <- which.min(enddts) adt <- enddts[enddts_min_index] adtm <- lubridate::as_datetime(adt) ady <- as.numeric(adt - startdt + 1) data.frame( ARM = patient_info$ARM, STUDYID = patient_info$STUDYID, SITEID = patient_info$SITEID, USUBJID = patient_info$USUBJID, PARAMCD = \"AEREPTTE\", PARAM = \"Time to end of AE reporting period\", CNSR = 0, AVAL = lubridate::days(ady) / lubridate::years(1), AVALU = \"YEARS\", EVNTDESC = ifelse(enddts_min_index == 1, \"Completion or Discontinuation\", \"End of AE Reporting Period\"), CNSDTDSC = NA, ADTM = adtm, ADY = ady, stringsAsFactors = FALSE ) } paramcd_hy <- c(\"HYSTTEUL\", \"HYSTTEBL\") param_hy <- c(\"Time to Hy's Law Elevation in relation to ULN\", \"Time to Hy's Law Elevation in relation to Baseline\") param_init_list <- relvar_init(param_hy, paramcd_hy) adsl_hy <- dplyr::select(adsl, \"STUDYID\", \"USUBJID\", \"TRTSDTM\", \"SITEID\", \"ARM\") adaette_hy <- expand.grid( STUDYID = unique(adsl$STUDYID), USUBJID = adsl$USUBJID, PARAM = as.factor(param_init_list$relvar1), stringsAsFactors = FALSE ) adaette_hy <- dplyr::left_join(adaette_hy, adsl_hy, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\") %>% dplyr::mutate( PARAMCD = factor(rel_var( df = as.data.frame(adaette_hy), var_values = param_init_list$relvar2, related_var = \"PARAM\" )) ) %>% dplyr::mutate( CNSR = sample(c(0, 1), prob = c(0.1, 0.9), size = dplyr::n(), replace = TRUE), EVNTDESC = dplyr::if_else( .data$CNSR == 0, \"First Post-Baseline Raised ALT or AST Elevation Result\", NA_character_ ), CNSDTDSC = dplyr::if_else(.data$CNSR == 0, NA_character_, sample(c(\"Last Post-Baseline ALT or AST Result\", \"Treatment Start\"), prob = c(0.9, 0.1), size = dplyr::n(), replace = TRUE ) ) ) %>% dplyr::rowwise() %>% dplyr::mutate(ADTM = dplyr::case_when( CNSDTDSC == \"Treatment Start\" ~ TRTSDTM, TRUE ~ TRTSDTM + sample(seq(0, study_duration_secs), size = dplyr::n(), replace = TRUE) )) %>% dplyr::mutate( ADY_int = lubridate::date(ADTM) - lubridate::date(TRTSDTM) + 1, ADY = as.numeric(ADY_int), AVAL = lubridate::days(ADY_int) / lubridate::weeks(1), AVALU = \"WEEKS\" ) %>% dplyr::select(-TRTSDTM, -ADY_int) random_ae_data <- function(lookup_info, patient_info, patient_data) { cnsr <- sample(c(0, 1), 1, prob = c(1 - lookup_info$CNSR_P, lookup_info$CNSR_P)) ae_rep_tte <- patient_data$AVAL[patient_data$PARAMCD == \"AEREPTTE\"] data.frame( ARM = rep(patient_data$ARM, 2), STUDYID = rep(patient_data$STUDYID, 2), SITEID = rep(patient_data$SITEID, 2), USUBJID = rep(patient_data$USUBJID, 2), PARAMCD = c( paste0(\"AETTE\", lookup_info$CATCD), paste0(\"AETOT\", lookup_info$CATCD) ), PARAM = c( paste(\"Time to first occurrence of\", lookup_info$CAT), paste(\"Number of occurrences of\", lookup_info$CAT) ), CNSR = c(cnsr, NA), AVAL = c( ifelse(cnsr == 1, ae_rep_tte, rtexp(1, lookup_info$LAMBDA * 365.25, r = ae_rep_tte)), ifelse(cnsr == 1, 0, rtpois(1, lookup_info$LAMBDA * 365.25)) ), AVALU = c(\"YEARS\", NA), EVNTDESC = c(ifelse(cnsr == 0, sample(evntdescr_sel, 1), \"\"), NA), CNSDTDSC = c(ifelse(cnsr == 1, sample(cnsdtdscr_sel, 1), \"\"), NA), stringsAsFactors = FALSE ) %>% dplyr::mutate( ADY = dplyr::if_else(is.na(AVALU), NA_real_, ceiling(as.numeric(lubridate::dyears(AVAL), \"days\"))), ADTM = dplyr::if_else( is.na(AVALU), lubridate::as_datetime(NA), patient_info$TRTSDTM + lubridate::days(ADY) ) ) } adaette <- split(adsl, adsl$USUBJID) %>% lapply(function(patient_info) { patient_data <- random_patient_data(patient_info) lookup_arm <- lookup_adaette %>% dplyr::filter(.data$ARM == as.character(patient_info$ARMCD)) ae_data <- split(lookup_arm, lookup_arm$CATCD) %>% lapply(random_ae_data, patient_data = patient_data, patient_info = patient_info) %>% Reduce(rbind, .) dplyr::bind_rows(patient_data, ae_data) }) %>% Reduce(rbind, .) adaette <- rbind(adaette, adaette_hy) tmc_ex_adaette <- adsl %>% dplyr::inner_join( dplyr::select(adaette, -\"SITEID\", -\"ARM\"), by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::group_by(.data$USUBJID) %>% dplyr::arrange(.data$ADTM) %>% dplyr::mutate(PARAM = as.factor(.data$PARAM)) %>% dplyr::mutate(PARAMCD = as.factor(.data$PARAMCD)) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$ADTM ) i_lbls <- sapply( names(col_labels(tmc_ex_adaette)[is.na(col_labels(tmc_ex_adaette))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adaette[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adaette, file = \"data/tmc_ex_adaette.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"adcm","dir":"Articles","previous_headings":"","what":"ADCM","title":"Example Data Generation","text":"","code":"generate_adcm <- function(adsl = tmc_ex_adsl, max_n_cms = 5L) { set.seed(1) lookup_cm <- tibble::tribble( ~CMCLAS, ~CMDECOD, ~ATIREL, \"medcl A\", \"medname A_1/3\", \"PRIOR\", \"medcl A\", \"medname A_2/3\", \"CONCOMITANT\", \"medcl A\", \"medname A_3/3\", \"CONCOMITANT\", \"medcl B\", \"medname B_1/4\", \"CONCOMITANT\", \"medcl B\", \"medname B_2/4\", \"PRIOR\", \"medcl B\", \"medname B_3/4\", \"PRIOR\", \"medcl B\", \"medname B_4/4\", \"CONCOMITANT\", \"medcl C\", \"medname C_1/2\", \"CONCOMITANT\", \"medcl C\", \"medname C_2/2\", \"CONCOMITANT\" ) adcm <- Map(function(id, sid) { n_cms <- sample(c(0, seq_len(max_n_cms)), 1) i <- sample(seq_len(nrow(lookup_cm)), n_cms, TRUE) dplyr::mutate( lookup_cm[i, ], USUBJID = id, STUDYID = sid ) }, adsl$USUBJID, adsl$STUDYID) %>% Reduce(rbind, .) %>% `[`(c(4, 5, 1, 2, 3)) %>% dplyr::mutate(CMCAT = .data$CMCLAS %>% with_label(\"Category for Medication\")) # merge adsl to be able to add CM date and study day variables adcm <- dplyr::inner_join( adcm, adsl, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::mutate(ASTDTM = sample( seq(lubridate::as_datetime(TRTSDTM), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1 )) %>% dplyr::mutate(ASTDY = ceiling(difftime(ASTDTM, TRTSDTM, units = \"days\"))) %>% # add 1 to end of range incase both values passed to sample() are the same dplyr::mutate(AENDTM = sample( seq(lubridate::as_datetime(ASTDTM), lubridate::as_datetime(TRTENDT + 1), by = \"day\"), size = 1 )) %>% dplyr::mutate(AENDY = ceiling(difftime(AENDTM, TRTSDTM, units = \"days\"))) %>% dplyr::select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(STUDYID, USUBJID, ASTDTM) tmc_ex_adcm <- adcm %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(CMSEQ = seq_len(dplyr::n())) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ASTDTM, .data$CMSEQ) %>% dplyr::mutate( ATC1 = paste(\"ATCCLAS1\", substr(.data$CMDECOD, 9, 9)) %>% with_label(\"ATC Level 1 Text\"), ATC2 = paste(\"ATCCLAS2\", substr(.data$CMDECOD, 9, 9)) %>% with_label(\"ATC Level 2 Text\"), ATC3 = paste(\"ATCCLAS3\", substr(.data$CMDECOD, 9, 9)) %>% with_label(\"ATC Level 3 Text\"), ATC4 = paste(\"ATCCLAS4\", substr(.data$CMDECOD, 9, 9)) %>% with_label(\"ATC Level 4 Text\") ) %>% dplyr::mutate( CMINDC = sample(c( \"Nausea\", \"Hypertension\", \"Urticaria\", \"Fever\", \"Asthma\", \"Infection\", \"Diabete\", \"Diarrhea\", \"Pneumonia\" ), dplyr::n(), replace = TRUE) %>% with_label(\"Indication\"), CMDOSE = sample(1:99, dplyr::n(), replace = TRUE) %>% with_label(\"Dose per Administration\"), CMTRT = substr(.data$CMDECOD, 9, 13) %>% with_label(\"Reported Name of Drug, Med, or Therapy\"), CMDOSU = sample(c( \"ug/mL\", \"ug/kg/day\", \"%\", \"uL\", \"DROP\", \"umol/L\", \"mg\", \"mg/breath\", \"ug\" ), dplyr::n(), replace = TRUE) %>% with_label(\"Dose Units\") ) %>% dplyr::mutate( CMROUTE = sample(c( \"INTRAVENOUS\", \"ORAL\", \"NASAL\", \"INTRAMUSCULAR\", \"SUBCUTANEOUS\", \"INHALED\", \"RECTAL\", \"UNKNOWN\" ), dplyr::n(), replace = TRUE) %>% with_label(\"Route of Administration\"), CMDOSFRQ = sample(c( \"Q4W\", \"QN\", \"Q4H\", \"UNKNOWN\", \"TWICE\", \"Q4H\", \"QD\", \"TID\", \"4 TIMES PER MONTH\" ), dplyr::n(), replace = TRUE) %>% with_label(\"Dosing Frequency per Interval\") ) %>% col_relabel( CMCLAS = \"Medication Class\", CMDECOD = \"Standardized Medication Name\", ATIREL = \"Time Relation of Medication\", CMSEQ = \"Sponsor-Defined Identifier\" ) i_lbls <- sapply( names(col_labels(tmc_ex_adcm)[is.na(col_labels(tmc_ex_adcm))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adcm[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adcm, file = \"data/tmc_ex_adcm.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"adeg","dir":"Articles","previous_headings":"","what":"ADEG","title":"Example Data Generation","text":"","code":"generate_adeg <- function(adsl = tmc_ex_adsl, n_assessments = 3L, n_days = 3L, max_n_eg = 3L) { set.seed(1) param <- c(\"QT Duration\", \"RR Duration\", \"Heart Rate\", \"ECG Interpretation\") paramcd <- c(\"QT\", \"RR\", \"HR\", \"ECGINTP\") paramu <- c(\"msec\", \"msec\", \"beats/min\", \"\") visit_format <- \"WEEK\" param_init_list <- relvar_init(param, paramcd) unit_init_list <- relvar_init(param, paramu) adeg <- expand.grid( STUDYID = unique(adsl$STUDYID), USUBJID = adsl$USUBJID, PARAM = as.factor(param_init_list$relvar1), AVISIT = visit_schedule(visit_format = visit_format, n_assessments = n_assessments, n_days = n_days), stringsAsFactors = FALSE ) adeg$PARAMCD <- as.factor(rel_var( df = adeg, var_name = \"PARAMCD\", var_values = param_init_list$relvar2, related_var = \"PARAM\" )) adeg <- adeg %>% dplyr::mutate(AVAL = dplyr::case_when( .data$PARAMCD == \"QT\" ~ stats::rnorm(nrow(adeg), mean = 350, sd = 100), .data$PARAMCD == \"RR\" ~ stats::rnorm(nrow(adeg), mean = 1050, sd = 300), .data$PARAMCD == \"HR\" ~ stats::rnorm(nrow(adeg), mean = 70, sd = 20), .data$PARAMCD == \"ECGINTP\" ~ NA_real_ )) adeg <- adeg %>% dplyr::mutate(AVISITN = dplyr::case_when( AVISIT == \"SCREENING\" ~ -1, AVISIT == \"BASELINE\" ~ 0, (grepl(\"^WEEK\", AVISIT) | grepl(\"^CYCLE\", AVISIT)) ~ as.numeric(AVISIT) - 2, TRUE ~ NA_real_ )) adeg$AVALU <- as.factor(rel_var( df = adeg, var_name = \"AVALU\", var_values = unit_init_list$relvar2, related_var = \"PARAM\" )) adeg <- adeg[order(adeg$STUDYID, adeg$USUBJID, adeg$PARAMCD, adeg$AVISITN), ] adeg <- Reduce(rbind, lapply(split(adeg, adeg$USUBJID), function(x) { x$STUDYID <- adsl$STUDYID[which(adsl$USUBJID == x$USUBJID[1])] x$ABLFL <- ifelse(toupper(visit_format) == \"WEEK\" & x$AVISIT == \"BASELINE\", \"Y\", ifelse(toupper(visit_format) == \"CYCLE\" & x$AVISIT == \"CYCLE 1 DAY 1\", \"Y\", \"\") ) x })) adeg$BASE <- ifelse(adeg$AVISITN >= 0, retain(adeg, adeg$AVAL, adeg$ABLFL == \"Y\"), adeg$AVAL) adeg <- adeg %>% dplyr::mutate(ANRLO = dplyr::case_when( .data$PARAMCD == \"QT\" ~ 200, .data$PARAMCD == \"RR\" ~ 600, .data$PARAMCD == \"HR\" ~ 40, .data$PARAMCD == \"ECGINTP\" ~ NA_real_ )) %>% dplyr::mutate(ANRHI = dplyr::case_when( .data$PARAMCD == \"QT\" ~ 500, .data$PARAMCD == \"RR\" ~ 1500, .data$PARAMCD == \"HR\" ~ 100, .data$PARAMCD == \"ECGINTP\" ~ NA_real_ )) %>% dplyr::mutate(ANRIND = factor(dplyr::case_when( .data$AVAL < .data$ANRLO ~ \"LOW\", .data$AVAL >= .data$ANRLO & .data$AVAL <= .data$ANRHI ~ \"NORMAL\", .data$AVAL > .data$ANRHI ~ \"HIGH\" ))) adeg <- adeg %>% dplyr::mutate(CHG = ifelse(.data$AVISITN > 0, .data$AVAL - .data$BASE, NA)) %>% dplyr::mutate(PCHG = ifelse(.data$AVISITN > 0, 100 * (.data$CHG / .data$BASE), NA)) %>% dplyr::mutate(BASETYPE = \"LAST\") %>% dplyr::group_by(.data$USUBJID, .data$PARAMCD, .data$BASETYPE) %>% dplyr::mutate(BNRIND = .data$ANRIND[.data$ABLFL == \"Y\"]) %>% dplyr::ungroup() %>% dplyr::mutate(DTYPE = NA) adeg$ANRIND <- factor(adeg$ANRIND, levels = c(\"LOW\", \"NORMAL\", \"HIGH\")) adeg$BNRIND <- factor(adeg$BNRIND, levels = c(\"LOW\", \"NORMAL\", \"HIGH\")) adeg <- dplyr::inner_join( adsl, adeg, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::ungroup() %>% dplyr::group_by(USUBJID) %>% dplyr::arrange(USUBJID, AVISITN) %>% dplyr::mutate(ADTM = rep( sort(sample( seq(lubridate::as_datetime(TRTSDTM[1]), lubridate::as_datetime(TRTENDT[1]), by = \"day\"), size = nlevels(AVISIT) )), each = n() / nlevels(AVISIT) )) %>% dplyr::ungroup() %>% dplyr::select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ADTM) adeg <- adeg %>% dplyr::group_by(.data$USUBJID) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$BASETYPE, .data$AVISITN, .data$DTYPE, .data$ADTM ) adeg <- adeg %>% dplyr::mutate(ONTRTFL = factor(dplyr::case_when( is.na(.data$TRTSDTM) ~ \"\", is.na(.data$ADTM) ~ \"Y\", (.data$ADTM < .data$TRTSDTM) ~ \"\", (.data$ADTM > .data$TRTEDTM) ~ \"\", TRUE ~ \"Y\" ))) %>% dplyr::mutate(AVALC = ifelse( .data$PARAMCD == \"ECGINTP\", as.character(sample_fct(c(\"ABNORMAL\", \"NORMAL\"), nrow(adeg), prob = c(0.25, 0.75))), as.character(.data$AVAL) )) adeg <- adeg %>% dplyr::mutate(row_check = seq_len(nrow(adeg))) get_groups <- function(data, minimum) { data <- data %>% dplyr::group_by(.data$USUBJID, .data$PARAMCD, .data$BASETYPE) %>% dplyr::arrange(.data$ADTM) %>% dplyr::filter( (.data$AVISIT != \"BASELINE\" & .data$AVISIT != \"SCREENING\") & (.data$ONTRTFL == \"Y\" | .data$ADTM <= .data$TRTSDTM) ) %>% { if (minimum == TRUE) { dplyr::filter(., .data$AVAL == min(.data$AVAL)) %>% dplyr::mutate(., DTYPE = \"MINIMUM\", AVISIT = \"POST-BASELINE MINIMUM\") } else { dplyr::filter(., .data$AVAL == max(.data$AVAL)) %>% dplyr::mutate(., DTYPE = \"MAXIMUM\", AVISIT = \"POST-BASELINE MAXIMUM\") } } %>% dplyr::slice(1) %>% dplyr::ungroup() return(data) } lbls <- col_labels(adeg) adeg <- rbind(adeg, get_groups(adeg, TRUE), get_groups(adeg, FALSE)) %>% dplyr::arrange(.data$row_check) %>% dplyr::group_by(.data$USUBJID, .data$PARAMCD, .data$BASETYPE) %>% dplyr::arrange(.data$AVISIT, .by_group = TRUE) %>% dplyr::ungroup() col_labels(adeg) <- lbls adeg <- adeg[, -which(names(adeg) %in% c(\"row_check\"))] flag_variables <- function(data, worst_obs) { data_compare <- data %>% dplyr::mutate(row_check = seq_len(nrow(data))) data <- data_compare %>% { if (worst_obs == FALSE) { dplyr::group_by(., .data$USUBJID, .data$PARAMCD, .data$BASETYPE, .data$AVISIT) %>% dplyr::arrange(., .data$ADTM) } else { dplyr::group_by(., .data$USUBJID, .data$PARAMCD, .data$BASETYPE) } } %>% dplyr::filter( .data$AVISITN > 0 & (.data$ONTRTFL == \"Y\" | .data$ADTM <= .data$TRTSDTM) & is.na(.data$DTYPE) ) %>% { if (worst_obs == TRUE) { dplyr::arrange(., .data$AVALC) %>% dplyr::filter(., ifelse( .data$PARAMCD == \"ECGINTP\", ifelse(.data$AVALC == \"ABNORMAL\", .data$AVALC == \"ABNORMAL\", .data$AVALC == \"NORMAL\"), .data$AVAL == min(.data$AVAL) )) } else { dplyr::filter(., ifelse( .data$PARAMCD == \"ECGINTP\", .data$AVALC == \"ABNORMAL\" | .data$AVALC == \"NORMAL\", .data$AVAL == min(.data$AVAL) )) } } %>% dplyr::slice(1) %>% { if (worst_obs == TRUE) { dplyr::mutate(., new_var = dplyr::case_when( (.data$AVALC == \"ABNORMAL\" | .data$AVALC == \"NORMAL\") ~ \"Y\", (!is.na(.data$AVAL) & is.na(.data$DTYPE)) ~ \"Y\", TRUE ~ \"\" )) } else { dplyr::mutate(., new_var = dplyr::case_when( (.data$AVALC == \"ABNORMAL\" | .data$AVALC == \"NORMAL\") ~ \"Y\", (!is.na(.data$AVAL) & is.na(.data$DTYPE)) ~ \"Y\", TRUE ~ \"\" )) } } %>% dplyr::ungroup() data_compare$new_var <- ifelse(data_compare$row_check %in% data$row_check, \"Y\", \"\") data_compare <- data_compare[, -which(names(data_compare) %in% c(\"row_check\"))] return(data_compare) } adeg <- flag_variables(adeg, FALSE) %>% dplyr::rename(WORS01FL = \"new_var\") adeg <- flag_variables(adeg, TRUE) %>% dplyr::rename(WORS02FL = \"new_var\") tmc_ex_adeg <- adeg %>% dplyr::group_by(.data$USUBJID, .data$PARAMCD, .data$BASETYPE) %>% dplyr::mutate(BASEC = ifelse( .data$PARAMCD == \"ECGINTP\", .data$AVALC[.data$AVISIT == \"BASELINE\"], as.character(.data$BASE) )) %>% dplyr::ungroup() %>% col_relabel(BASEC = \"Baseline Character Value\") i_lbls <- sapply( names(col_labels(tmc_ex_adeg)[is.na(col_labels(tmc_ex_adeg))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adeg[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adeg, file = \"data/tmc_ex_adeg.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"adex","dir":"Articles","previous_headings":"","what":"ADEX","title":"Example Data Generation","text":"","code":"generate_adex <- function(adsl = tmc_ex_adsl, n_assessments = 3L, n_days = 3L, max_n_exs = 3L) { set.seed(1) param <- c( \"Dose administered during constant dosing interval\", \"Number of doses administered during constant dosing interval\", \"Total dose administered\", \"Total number of doses administered\" ) paramcd <- c(\"DOSE\", \"NDOSE\", \"TDOSE\", \"TNDOSE\") paramu <- c(\"mg\", \" \", \"mg\", \" \") parcat1 <- c(\"INDIVIDUAL\", \"OVERALL\") parcat2 <- c(\"Drug A\", \"Drug B\") visit_format <- \"WEEK\" param_init_list <- relvar_init(param, paramcd) unit_init_list <- relvar_init(param, paramu) adex <- expand.grid( STUDYID = unique(adsl$STUDYID), USUBJID = adsl$USUBJID, PARAM = c( rep( param_init_list$relvar1[1], length(levels(visit_schedule(visit_format = visit_format, n_assessments = n_assessments, n_days = n_days))) ), rep( param_init_list$relvar1[2], length(levels(visit_schedule(visit_format = visit_format, n_assessments = n_assessments, n_days = n_days))) ), param_init_list$relvar1[3:4] ), stringsAsFactors = FALSE ) adex$PARAMCD <- as.factor(rel_var( df = adex, var_name = \"PARAMCD\", var_values = param_init_list$relvar2, related_var = \"PARAM\" )) adex$AVALU <- as.factor(rel_var( df = adex, var_name = \"AVALU\", var_values = unit_init_list$relvar2, related_var = \"PARAM\" )) adex <- adex %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(PARCAT_ind = sample(c(1, 2), size = 1)) %>% dplyr::mutate(PARCAT2 = ifelse(.data$PARCAT_ind == 1, parcat2[1], parcat2[2])) %>% dplyr::select(-\"PARCAT_ind\") adex <- adex %>% dplyr::mutate(PARCAT1 = dplyr::case_when( (.data$PARAMCD == \"TNDOSE\" | .data$PARAMCD == \"TDOSE\") ~ \"OVERALL\", .data$PARAMCD == \"DOSE\" | .data$PARAMCD == \"NDOSE\" ~ \"INDIVIDUAL\" )) adex_visit <- adex %>% dplyr::filter(.data$PARAMCD == \"DOSE\" | .data$PARAMCD == \"NDOSE\") %>% dplyr::mutate( AVISIT = rep(visit_schedule(visit_format = visit_format, n_assessments = n_assessments, n_days = n_days), 2) ) adex <- dplyr::left_join( adex %>% dplyr::group_by( .data$USUBJID, .data$STUDYID, .data$PARAM, .data$PARAMCD, .data$AVALU, .data$PARCAT1, .data$PARCAT2 ) %>% dplyr::mutate(id = dplyr::row_number()), adex_visit %>% dplyr::group_by( .data$USUBJID, .data$STUDYID, .data$PARAM, .data$PARAMCD, .data$AVALU, .data$PARCAT1, .data$PARCAT2 ) %>% dplyr::mutate(id = dplyr::row_number()), by = c(\"USUBJID\", \"STUDYID\", \"PARCAT1\", \"PARCAT2\", \"id\", \"PARAMCD\", \"PARAM\", \"AVALU\") ) %>% dplyr::select(-\"id\") adex <- adex %>% dplyr::mutate(AVISITN = dplyr::case_when( AVISIT == \"SCREENING\" ~ -1, AVISIT == \"BASELINE\" ~ 0, (grepl(\"^WEEK\", AVISIT) | grepl(\"^CYCLE\", AVISIT)) ~ as.numeric(AVISIT) - 2, TRUE ~ 999000 )) adex2 <- split(adex, adex$USUBJID) %>% lapply(function(pinfo) { pinfo %>% dplyr::filter(.data$PARAMCD == \"DOSE\") %>% dplyr::group_by(.data$USUBJID, .data$PARCAT2, .data$AVISIT) %>% dplyr::mutate(changeind = dplyr::case_when( .data$AVISIT == \"SCREENING\" ~ 0, .data$AVISIT != \"SCREENING\" ~ sample(c(-1, 0, 1), size = 1, prob = c(0.25, 0.5, 0.25), replace = TRUE ) )) %>% dplyr::ungroup() %>% dplyr::group_by(.data$USUBJID, .data$PARCAT2) %>% dplyr::mutate( csum = cumsum(.data$changeind), changeind = dplyr::case_when( .data$csum <= -3 ~ sample(c(0, 1), size = 1, prob = c(0.5, 0.5)), .data$csum >= 3 ~ sample(c(0, -1), size = 1, prob = c(0.5, 0.5)), TRUE ~ .data$changeind ) ) %>% dplyr::mutate(csum = cumsum(.data$changeind)) %>% dplyr::ungroup() %>% dplyr::group_by(.data$USUBJID, .data$PARCAT2, .data$AVISIT) %>% dplyr::mutate(AVAL = dplyr::case_when( .data$csum == -2 ~ 480, .data$csum == -1 ~ 720, .data$csum == 0 ~ 960, .data$csum == 1 ~ 1200, .data$csum == 2 ~ 1440 )) %>% dplyr::select(-c(\"csum\", \"changeind\")) %>% dplyr::ungroup() }) %>% Reduce(rbind, .) adextmp <- dplyr::full_join(adex2, adex, by = names(adex)) adex <- adextmp %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(AVAL = ifelse(.data$PARAMCD == \"NDOSE\", 1, .data$AVAL)) %>% dplyr::mutate(AVAL = ifelse( .data$PARAMCD == \"TNDOSE\", sum(.data$AVAL[.data$PARAMCD == \"NDOSE\"]), .data$AVAL )) %>% dplyr::ungroup() %>% dplyr::group_by(.data$USUBJID, .data$STUDYID, .data$PARCAT2) %>% dplyr::mutate(AVAL = ifelse( .data$PARAMCD == \"TDOSE\", sum(.data$AVAL[.data$PARAMCD == \"DOSE\"]), .data$AVAL )) adex <- dplyr::inner_join(adsl, adex, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\") %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::mutate(ASTDTM = sample( seq(lubridate::as_datetime(TRTSDTM), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1 )) %>% dplyr::select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ASTDTM) adex <- adex %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(EXSEQ = seq_len(dplyr::n())) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$ASTDTM, .data$AVISITN ) %>% col_relabel( PARCAT1 = \"Parameter Category (Individual/Overall)\", PARCAT2 = \"Parameter Category (Drug A/Drug B)\", EXSEQ = \"Analysis Sequence Number\" ) visit_levels <- str_extract(levels(adex$AVISIT), pattern = \"[0-9]+\") vl_extracted <- vapply(visit_levels, function(x) as.numeric(x[2]), numeric(1)) vl_extracted <- c(-1, 1, vl_extracted[!is.na(vl_extracted)]) tmc_ex_adex <- adex %>% dplyr::mutate(VISITDY = as.numeric(as.character(factor(AVISIT, labels = vl_extracted)))) %>% dplyr::mutate(ASTDTM = lubridate::as_datetime(TRTSDTM) + lubridate::days(VISITDY)) %>% dplyr::distinct(USUBJID, .keep_all = TRUE) i_lbls <- sapply( names(col_labels(tmc_ex_adex)[is.na(col_labels(tmc_ex_adex))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adex[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adex, file = \"data/tmc_ex_adex.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"adlb","dir":"Articles","previous_headings":"","what":"ADLB","title":"Example Data Generation","text":"","code":"generate_adlb <- function(adsl = tmc_ex_adsl, n_assessments = 3L, n_days = 3L, max_n_lbs = 3L) { set.seed(1) lbcat <- c(\"CHEMISTRY\", \"CHEMISTRY\", \"IMMUNOLOGY\") param <- c( \"Alanine Aminotransferase Measurement\", \"C-Reactive Protein Measurement\", \"Immunoglobulin A Measurement\" ) paramcd <- c(\"ALT\", \"CRP\", \"IGA\") paramu <- c(\"U/L\", \"mg/L\", \"g/L\") aval_mean <- c(20, 1, 2) visit_format <- \"WEEK\" # validate and initialize related variables lbcat_init_list <- relvar_init(param, lbcat) param_init_list <- relvar_init(param, paramcd) unit_init_list <- relvar_init(param, paramu) adlb <- expand.grid( STUDYID = unique(adsl$STUDYID), USUBJID = adsl$USUBJID, PARAM = as.factor(param_init_list$relvar1), AVISIT = visit_schedule(visit_format = visit_format, n_assessments = n_assessments, n_days = n_days), stringsAsFactors = FALSE ) # assign AVAL based on different test adlb <- adlb %>% dplyr::mutate(AVAL = stats::rnorm(nrow(adlb), mean = 1, sd = 0.2)) %>% dplyr::left_join(data.frame(PARAM = param, ADJUST = aval_mean), by = \"PARAM\") %>% dplyr::mutate(AVAL = .data$AVAL * .data$ADJUST) %>% dplyr::select(-\"ADJUST\") # assign related variable values: PARAMxLBCAT are related adlb$LBCAT <- as.factor(rel_var( df = adlb, var_name = \"LBCAT\", var_values = lbcat_init_list$relvar2, related_var = \"PARAM\" )) # assign related variable values: PARAMxPARAMCD are related adlb$PARAMCD <- as.factor(rel_var( df = adlb, var_name = \"PARAMCD\", var_values = param_init_list$relvar2, related_var = \"PARAM\" )) adlb$AVALU <- as.factor(rel_var( df = adlb, var_name = \"AVALU\", var_values = unit_init_list$relvar2, related_var = \"PARAM\" )) adlb <- adlb %>% dplyr::mutate(AVISITN = dplyr::case_when( AVISIT == \"SCREENING\" ~ -1, AVISIT == \"BASELINE\" ~ 0, (grepl(\"^WEEK\", AVISIT) | grepl(\"^CYCLE\", AVISIT)) ~ as.numeric(AVISIT) - 2, TRUE ~ NA_real_ )) adlb <- adlb %>% dplyr::mutate(AVISITN = dplyr::case_when( AVISIT == \"SCREENING\" ~ -1, AVISIT == \"BASELINE\" ~ 0, (grepl(\"^WEEK\", AVISIT) | grepl(\"^CYCLE\", AVISIT)) ~ as.numeric(AVISIT) - 2, TRUE ~ NA_real_ )) # order to prepare for change from screening and baseline values adlb <- adlb[order(adlb$STUDYID, adlb$USUBJID, adlb$PARAMCD, adlb$AVISITN), ] adlb <- Reduce(rbind, lapply(split(adlb, adlb$USUBJID), function(x) { x$STUDYID <- adsl$STUDYID[which(adsl$USUBJID == x$USUBJID[1])] x$ABLFL2 <- ifelse(x$AVISIT == \"SCREENING\", \"Y\", \"\") x$ABLFL <- ifelse(toupper(visit_format) == \"WEEK\" & x$AVISIT == \"BASELINE\", \"Y\", ifelse(toupper(visit_format) == \"CYCLE\" & x$AVISIT == \"CYCLE 1 DAY 1\", \"Y\", \"\") ) x })) adlb$BASE <- ifelse(adlb$ABLFL2 != \"Y\", retain(adlb, adlb$AVAL, adlb$ABLFL == \"Y\"), NA) anrind_choices <- c(\"HIGH\", \"LOW\", \"NORMAL\") adlb <- adlb %>% dplyr::mutate(BASETYPE = \"LAST\") %>% dplyr::mutate(ANRIND = sample_fct(anrind_choices, nrow(adlb), prob = c(0.1, 0.1, 0.8))) %>% dplyr::mutate(ANRLO = dplyr::case_when( .data$PARAMCD == \"ALT\" ~ 7, .data$PARAMCD == \"CRP\" ~ 8, .data$PARAMCD == \"IGA\" ~ 0.8 )) %>% dplyr::mutate(ANRHI = dplyr::case_when( .data$PARAMCD == \"ALT\" ~ 55, .data$PARAMCD == \"CRP\" ~ 10, .data$PARAMCD == \"IGA\" ~ 3 )) %>% dplyr::mutate(DTYPE = NA) %>% dplyr::mutate( ATOXGR = factor(dplyr::case_when( .data$ANRIND == \"LOW\" ~ sample( c(\"-1\", \"-2\", \"-3\", \"-4\", \"-5\"), nrow(adlb), replace = TRUE, prob = c(0.30, 0.25, 0.20, 0.15, 0) ), .data$ANRIND == \"HIGH\" ~ sample( c(\"1\", \"2\", \"3\", \"4\", \"5\"), nrow(adlb), replace = TRUE, prob = c(0.30, 0.25, 0.20, 0.15, 0) ), .data$ANRIND == \"NORMAL\" ~ \"0\" )) %>% with_label(\"Analysis Toxicity Grade\") ) %>% dplyr::group_by(.data$USUBJID, .data$PARAMCD, .data$BASETYPE) %>% dplyr::mutate(BTOXGR = .data$ATOXGR[.data$ABLFL == \"Y\"]) %>% dplyr::ungroup() %>% col_relabel(BTOXGR = \"Baseline Toxicity Grade\") # High and low descriptions of the different PARAMCD values # This is currently hard coded as the GDSR does not have these descriptions yet grade_lookup <- tibble::tribble( ~PARAMCD, ~ATOXDSCL, ~ATOXDSCH, \"ALB\", \"Hypoalbuminemia\", NA_character_, \"ALKPH\", NA_character_, \"Alkaline phosphatase increased\", \"ALT\", NA_character_, \"Alanine aminotransferase increased\", \"AST\", NA_character_, \"Aspartate aminotransferase increased\", \"BILI\", NA_character_, \"Blood bilirubin increased\", \"CA\", \"Hypocalcemia\", \"Hypercalcemia\", \"CHOLES\", NA_character_, \"Cholesterol high\", \"CK\", NA_character_, \"CPK increased\", \"CREAT\", NA_character_, \"Creatinine increased\", \"CRP\", NA_character_, \"C reactive protein increased\", \"GGT\", NA_character_, \"GGT increased\", \"GLUC\", \"Hypoglycemia\", \"Hyperglycemia\", \"HGB\", \"Anemia\", \"Hemoglobin increased\", \"IGA\", NA_character_, \"Immunoglobulin A increased\", \"POTAS\", \"Hypokalemia\", \"Hyperkalemia\", \"LYMPH\", \"CD4 lymphocytes decreased\", NA_character_, \"PHOS\", \"Hypophosphatemia\", NA_character_, \"PLAT\", \"Platelet count decreased\", NA_character_, \"SODIUM\", \"Hyponatremia\", \"Hypernatremia\", \"WBC\", \"White blood cell decreased\", \"Leukocytosis\", ) # merge grade_lookup onto adlb adlb <- dplyr::left_join(adlb, grade_lookup, by = \"PARAMCD\") # merge adsl to be able to add LB date and study day variables adlb <- dplyr::inner_join( adsl, adlb, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::ungroup() %>% dplyr::group_by(USUBJID) %>% dplyr::arrange(USUBJID, AVISITN) %>% dplyr::mutate(ADTM = rep( sort(sample( seq(lubridate::as_datetime(TRTSDTM[1]), lubridate::as_datetime(TRTENDT[1]), by = \"day\"), size = nlevels(AVISIT) )), each = n() / nlevels(AVISIT) )) %>% dplyr::ungroup() %>% dplyr::select(-TRTENDT) %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ADTM) adlb <- adlb %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(LBSEQ = seq_len(dplyr::n())) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$BASETYPE, .data$AVISITN, .data$DTYPE, .data$ADTM, .data$LBSEQ ) %>% col_relabel(LBSEQ = \"Lab Test or Examination Sequence Number\") adlb <- adlb %>% dplyr::mutate(ONTRTFL = factor(dplyr::case_when( is.na(.data$TRTSDTM) ~ \"\", is.na(.data$ADTM) ~ \"Y\", (.data$ADTM < .data$TRTSDTM) ~ \"\", (.data$ADTM > .data$TRTEDTM) ~ \"\", TRUE ~ \"Y\" ))) flag_variables <- function(data, apply_grouping, apply_filter, apply_mutate) { data_compare <- data %>% dplyr::mutate(row_check = seq_len(nrow(data))) data <- data_compare %>% { if (apply_grouping == TRUE) { dplyr::group_by(., .data$USUBJID, .data$PARAMCD, .data$BASETYPE, .data$AVISIT) } else { dplyr::group_by(., .data$USUBJID, .data$PARAMCD, .data$BASETYPE) } } %>% dplyr::arrange(.data$ADTM, .data$LBSEQ) %>% { if (apply_filter == TRUE) { dplyr::filter( ., (.data$AVISIT != \"BASELINE\" & .data$AVISIT != \"SCREENING\") & (.data$ONTRTFL == \"Y\" | .data$ADTM <= .data$TRTSDTM) ) %>% dplyr::filter(.data$ATOXGR == max(as.numeric(as.character(.data$ATOXGR)))) } else if (apply_filter == FALSE) { dplyr::filter( ., (.data$AVISIT != \"BASELINE\" & .data$AVISIT != \"SCREENING\") & (.data$ONTRTFL == \"Y\" | .data$ADTM <= .data$TRTSDTM) ) %>% dplyr::filter(.data$ATOXGR == min(as.numeric(as.character(.data$ATOXGR)))) } else { dplyr::filter( ., .data$AVAL == min(.data$AVAL) & (.data$AVISIT != \"BASELINE\" & .data$AVISIT != \"SCREENING\") & (.data$ONTRTFL == \"Y\" | .data$ADTM <= .data$TRTSDTM) ) } } %>% dplyr::slice(1) %>% { if (apply_mutate == TRUE) { dplyr::mutate(., new_var = ifelse(is.na(.data$DTYPE), \"Y\", \"\")) } else { dplyr::mutate(., new_var = ifelse(is.na(.data$AVAL) == FALSE & is.na(.data$DTYPE), \"Y\", \"\")) } } %>% dplyr::ungroup() data_compare$new_var <- ifelse(data_compare$row_check %in% data$row_check, \"Y\", \"\") data_compare <- data_compare[, -which(names(data_compare) %in% c(\"row_check\"))] return(data_compare) } adlb <- flag_variables(adlb, TRUE, \"ELSE\", FALSE) %>% dplyr::rename(WORS01FL = \"new_var\") adlb <- flag_variables(adlb, FALSE, TRUE, TRUE) %>% dplyr::rename(WGRHIFL = \"new_var\") adlb <- flag_variables(adlb, FALSE, FALSE, TRUE) %>% dplyr::rename(WGRLOFL = \"new_var\") adlb <- flag_variables(adlb, TRUE, TRUE, TRUE) %>% dplyr::rename(WGRHIVFL = \"new_var\") adlb <- flag_variables(adlb, TRUE, FALSE, TRUE) %>% dplyr::rename(WGRLOVFL = \"new_var\") tmc_ex_adlb <- adlb %>% dplyr::mutate( ANL01FL = ifelse( (.data$ABLFL == \"Y\" | (.data$WORS01FL == \"Y\" & is.na(.data$DTYPE))) & (.data$AVISIT != \"SCREENING\"), \"Y\", \"\" ) %>% with_label(\"Analysis Flag 01 Baseline Post-Baseline\"), PARAM = as.factor(.data$PARAM) ) tmc_ex_adlb <- tmc_ex_adlb %>% group_by(.data$USUBJID, .data$PARAMCD, .data$BASETYPE) %>% mutate(BNRIND = .data$ANRIND[.data$ABLFL == \"Y\"]) %>% ungroup() %>% dplyr::mutate(ADY = ceiling(as.numeric(difftime(.data$ADTM, .data$TRTSDTM, units = \"days\")))) tmc_ex_adlb$PARAMCD <- as.factor(tmc_ex_adlb$PARAMCD) tmc_ex_adlb <- tmc_ex_adlb %>% dplyr::mutate(CHG = .data$AVAL - .data$BASE) %>% dplyr::mutate(PCHG = 100 * (.data$CHG / .data$BASE)) %>% col_relabel( LBCAT = \"Category for Lab Test\", ATOXDSCL = \"Analysis Toxicity Description Low\", ATOXDSCH = \"Analysis Toxicity Description High\", WGRHIFL = \"Worst High Grade per Patient\", WGRLOFL = \"Worst Low Grade per Patient\", WGRHIVFL = \"Worst High Grade per Patient per Visit\", WGRLOVFL = \"Worst Low Grade per Patient per Visit\" ) i_lbls <- sapply( names(col_labels(tmc_ex_adlb)[is.na(col_labels(tmc_ex_adlb))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adlb[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adlb, file = \"data/tmc_ex_adlb.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"admh","dir":"Articles","previous_headings":"","what":"ADMH","title":"Example Data Generation","text":"","code":"generate_admh <- function(adsl = tmc_ex_adsl, max_n_mhs = 10L) { set.seed(1) lookup_mh <- tibble::tribble( ~MHBODSYS, ~MHDECOD, ~MHSOC, \"cl A\", \"trm A_1/2\", \"cl A\", \"cl A\", \"trm A_2/2\", \"cl A\", \"cl B\", \"trm B_1/3\", \"cl B\", \"cl B\", \"trm B_2/3\", \"cl B\", \"cl B\", \"trm B_3/3\", \"cl B\", \"cl C\", \"trm C_1/2\", \"cl C\", \"cl C\", \"trm C_2/2\", \"cl C\", \"cl D\", \"trm D_1/3\", \"cl D\", \"cl D\", \"trm D_2/3\", \"cl D\", \"cl D\", \"trm D_3/3\", \"cl D\" ) admh <- Map( function(id, sid) { n_mhs <- sample(0:max_n_mhs, 1) i <- sample(seq_len(nrow(lookup_mh)), n_mhs, TRUE) dplyr::mutate( lookup_mh[i, ], USUBJID = id, STUDYID = sid ) }, adsl$USUBJID, adsl$STUDYID ) %>% Reduce(rbind, .) %>% `[`(c(4, 5, 1, 2, 3)) %>% dplyr::mutate(MHTERM = .data$MHDECOD %>% with_label(\"Reported Term for the Medical History\")) admh <- dplyr::inner_join( adsl, admh, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::mutate(ASTDTM = sample( seq(lubridate::as_datetime(TRTSDTM), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1 )) %>% select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ASTDTM, .data$MHTERM) %>% dplyr::mutate(MHDISTAT = sample( x = c(\"Resolved\", \"Ongoing with treatment\", \"Ongoing without treatment\"), prob = c(0.6, 0.2, 0.2), size = dplyr::n(), replace = TRUE ) %>% with_label(\"Status of Disease\")) tmc_ex_admh <- admh %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(MHSEQ = seq_len(dplyr::n())) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ASTDTM) %>% col_relabel( MHBODSYS = \"Body System or Organ Class\", MHDECOD = \"Dictionary-Derived Term\", MHSOC = \"Primary System Organ Class\", MHSEQ = \"Sponsor-Defined Identifier\" ) i_lbls <- sapply( names(col_labels(tmc_ex_admh)[is.na(col_labels(tmc_ex_admh))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_admh[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_admh, file = \"data/tmc_ex_admh.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"adqs","dir":"Articles","previous_headings":"","what":"ADQS","title":"Example Data Generation","text":"","code":"generate_adqs <- function(adsl = tmc_ex_adsl, n_assessments = 5L, n_days = 5L) { set.seed(1) param <- c( \"BFI All Questions\", \"Fatigue Interference\", \"Function/Well-Being (GF1,GF3,GF7)\", \"Treatment Side Effects (GP2,C5,GP5)\", \"FKSI-19 All Questions\" ) paramcd <- c(\"BFIALL\", \"FATIGI\", \"FKSI-FWB\", \"FKSI-TSE\", \"FKSIALL\") visit_format <- \"WEEK\" param_init_list <- relvar_init(param, paramcd) adqs <- expand.grid( STUDYID = unique(adsl$STUDYID), USUBJID = adsl$USUBJID, PARAM = param_init_list$relvar1, AVISIT = visit_schedule(visit_format = visit_format, n_assessments = n_assessments, n_days = n_days), stringsAsFactors = FALSE ) adqs <- dplyr::mutate( adqs, AVISITN = dplyr::case_when( AVISIT == \"SCREENING\" ~ -1, AVISIT == \"BASELINE\" ~ 0, (grepl(\"^WEEK\", AVISIT) | grepl(\"^CYCLE\", AVISIT)) ~ as.numeric(AVISIT) - 2, TRUE ~ NA_real_ ) ) adqs$PARAMCD <- rel_var(df = adqs, var_name = \"PARAMCD\", var_values = param_init_list$relvar2, related_var = \"PARAM\") adqs$AVAL <- stats::rnorm(nrow(adqs), mean = 50, sd = 8) + adqs$AVISITN * stats::rnorm(nrow(adqs), mean = 5, sd = 2) adqs <- adqs[order(adqs$STUDYID, adqs$USUBJID, adqs$PARAMCD, adqs$AVISITN), ] adqs <- Reduce( rbind, lapply( split(adqs, adqs$USUBJID), function(x) { x$STUDYID <- adsl$STUDYID[which(adsl$USUBJID == x$USUBJID[1])] x$ABLFL2 <- ifelse(x$AVISIT == \"SCREENING\", \"Y\", \"\") x$ABLFL <- ifelse( toupper(visit_format) == \"WEEK\" & x$AVISIT == \"BASELINE\", \"Y\", ifelse( toupper(visit_format) == \"CYCLE\" & x$AVISIT == \"CYCLE 1 DAY 1\", \"Y\", \"\" ) ) x } ) ) adqs$BASE <- ifelse(adqs$ABLFL2 != \"Y\", retain(adqs, adqs$AVAL, adqs$ABLFL == \"Y\"), NA) adqs <- adqs %>% dplyr::mutate(CHG = .data$AVAL - .data$BASE) adqs <- dplyr::inner_join( adsl, adqs, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% ungroup() %>% group_by(USUBJID) %>% arrange(USUBJID, AVISITN) %>% dplyr::mutate(ADTM = rep( sort(sample( seq(lubridate::as_datetime(TRTSDTM[1]), lubridate::as_datetime(TRTENDT[1]), by = \"day\"), size = nlevels(AVISIT) )), each = n() / nlevels(AVISIT) )) %>% dplyr::ungroup() %>% dplyr::select(-TRTENDT) %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ADTM) tmc_ex_adqs <- adqs %>% dplyr::group_by(.data$USUBJID) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$AVISITN, .data$ADTM ) i_lbls <- sapply( names(col_labels(tmc_ex_adqs)[is.na(col_labels(tmc_ex_adqs))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adqs[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adqs, file = \"data/tmc_ex_adqs.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"adrs","dir":"Articles","previous_headings":"","what":"ADRS","title":"Example Data Generation","text":"","code":"generate_adrs <- function(adsl = tmc_ex_adsl) { set.seed(1) param_codes <- stats::setNames(1:5, c(\"CR\", \"PR\", \"SD\", \"PD\", \"NE\")) lookup_ars <- expand.grid( ARM = c(\"A: Drug X\", \"B: Placebo\", \"C: Combination\"), AVALC = names(param_codes) ) %>% dplyr::mutate( AVAL = param_codes[.data$AVALC], p_scr = c(rep(0, 3), rep(0, 3), c(1, 1, 1), c(0, 0, 0), c(0, 0, 0)), p_bsl = c(rep(0, 3), rep(0, 3), c(1, 1, 1), c(0, 0, 0), c(0, 0, 0)), p_cycle = c(c(.35, .25, .4), c(.30, .20, .20), c(.2, .25, .3), c(.14, 0.20, 0.18), c(.01, 0.1, 0.02)), p_eoi = c(c(.35, .25, .4), c(.30, .20, .20), c(.2, .25, .3), c(.14, 0.20, 0.18), c(.01, 0.1, 0.02)), p_fu = c(c(.25, .15, .3), c(.15, .05, .25), c(.3, .25, .3), c(.3, .55, .25), rep(0, 3)) ) adrs <- split(adsl, adsl$USUBJID) %>% lapply(function(pinfo) { probs <- dplyr::filter(lookup_ars, .data$ARM == as.character(pinfo$ACTARM)) # screening rsp_screen <- sample(probs$AVALC, 1, prob = probs$p_scr) %>% as.character() # baseline rsp_bsl <- sample(probs$AVALC, 1, prob = probs$p_bsl) %>% as.character() # cycle rsp_c2d1 <- sample(probs$AVALC, 1, prob = probs$p_cycle) %>% as.character() rsp_c4d1 <- sample(probs$AVALC, 1, prob = probs$p_cycle) %>% as.character() # end of induction rsp_eoi <- sample(probs$AVALC, 1, prob = probs$p_eoi) %>% as.character() # follow up rsp_fu <- sample(probs$AVALC, 1, prob = probs$p_fu) %>% as.character() best_rsp <- min(param_codes[c(rsp_screen, rsp_bsl, rsp_eoi, rsp_fu, rsp_c2d1, rsp_c4d1)]) best_rsp_i <- which.min(param_codes[c(rsp_screen, rsp_bsl, rsp_eoi, rsp_fu, rsp_c2d1, rsp_c4d1)]) avisit <- c(\"SCREENING\", \"BASELINE\", \"CYCLE 2 DAY 1\", \"CYCLE 4 DAY 1\", \"END OF INDUCTION\", \"FOLLOW UP\") # meaningful date information TRTSTDT <- lubridate::date(pinfo$TRTSDTM) TRTENDT <- lubridate::date(dplyr::if_else( !is.na(pinfo$TRTEDTM), pinfo$TRTEDTM, lubridate::floor_date(TRTSTDT + study_duration_secs, unit = \"day\") )) scr_date <- TRTSTDT - lubridate::days(100) bs_date <- TRTSTDT flu_date <- sample(seq(lubridate::as_datetime(TRTSTDT), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1) eoi_date <- sample(seq(lubridate::as_datetime(TRTSTDT), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1) c2d1_date <- sample(seq(lubridate::as_datetime(TRTSTDT), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1) c4d1_date <- min(lubridate::date(c2d1_date + lubridate::days(60)), TRTENDT) tibble::tibble( STUDYID = pinfo$STUDYID, USUBJID = pinfo$USUBJID, PARAMCD = as.factor(c(rep(\"OVRINV\", 6), \"BESRSPI\", \"INVET\")), PARAM = as.factor(dplyr::recode( .data$PARAMCD, OVRINV = \"Overall Response by Investigator - by visit\", OVRSPI = \"Best Overall Response by Investigator (no confirmation required)\", BESRSPI = \"Best Confirmed Overall Response by Investigator\", INVET = \"Investigator End Of Induction Response\" )), AVALC = c( rsp_screen, rsp_bsl, rsp_c2d1, rsp_c4d1, rsp_eoi, rsp_fu, names(param_codes)[best_rsp], rsp_eoi ), AVAL = param_codes[.data$AVALC], AVISIT = factor(c(avisit, avisit[best_rsp_i], avisit[5]), levels = avisit) ) %>% merge( tibble::tibble( AVISIT = avisit, ADTM = c(scr_date, bs_date, c2d1_date, c4d1_date, eoi_date, flu_date), AVISITN = c(-1, 0, 2, 4, 999, 999), TRTSDTM = pinfo$TRTSDTM ) %>% dplyr::select(-\"TRTSDTM\"), by = \"AVISIT\" ) }) %>% Reduce(rbind, .) %>% dplyr::mutate( AVALC = factor(.data$AVALC, levels = names(param_codes)), DTHFL = factor(sample(c(\"Y\", \"N\"), nrow(.), replace = TRUE, prob = c(1, 0.8))) %>% with_label(\"Death Flag\") ) # merge ADSL to be able to add RS date and study day variables adrs <- dplyr::inner_join( adsl, adrs, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) tmc_ex_adrs <- adrs %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$AVISITN, .data$ADTM ) i_lbls <- sapply( names(col_labels(tmc_ex_adrs)[is.na(col_labels(tmc_ex_adrs))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adrs[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adrs, file = \"data/tmc_ex_adrs.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"adtte","dir":"Articles","previous_headings":"","what":"ADTTE","title":"Example Data Generation","text":"","code":"generate_adtte <- function(adsl = tmc_ex_adsl) { set.seed(1) lookup_tte <- tibble::tribble( ~ARM, ~PARAMCD, ~PARAM, ~LAMBDA, ~CNSR_P, \"ARM A\", \"OS\", \"Overall Survival\", log(2) / 610, 0.4, \"ARM B\", \"OS\", \"Overall Survival\", log(2) / 490, 0.3, \"ARM C\", \"OS\", \"Overall Survival\", log(2) / 365, 0.2, \"ARM A\", \"PFS\", \"Progression Free Survival\", log(2) / 365, 0.4, \"ARM B\", \"PFS\", \"Progression Free Survival\", log(2) / 305, 0.3, \"ARM C\", \"PFS\", \"Progression Free Survival\", log(2) / 243, 0.2, \"ARM A\", \"EFS\", \"Event Free Survival\", log(2) / 365, 0.4, \"ARM B\", \"EFS\", \"Event Free Survival\", log(2) / 305, 0.3, \"ARM C\", \"EFS\", \"Event Free Survival\", log(2) / 243, 0.2, \"ARM A\", \"CRSD\", \"Duration of Confirmed Response\", log(2) / 305, 0.4, \"ARM B\", \"CRSD\", \"Duration of Confirmed Response\", log(2) / 243, 0.3, \"ARM C\", \"CRSD\", \"Duration of Confirmed Response\", log(2) / 182, 0.2 ) evntdescr_sel <- c( \"Death\", \"Disease Progression\", \"Last Tumor Assessment\", \"Adverse Event\", \"Last Date Known To Be Alive\" ) cnsdtdscr_sel <- c( \"Preferred Term\", \"Clinical Cut Off\", \"Completion or Discontinuation\", \"End of AE Reporting Period\" ) adtte <- split(adsl, adsl$USUBJID) %>% lapply(FUN = function(pinfo) { lookup_tte %>% dplyr::filter(.data$ARM == as.character(pinfo$ACTARMCD)) %>% dplyr::rowwise() %>% dplyr::mutate( STUDYID = pinfo$STUDYID, USUBJID = pinfo$USUBJID, CNSR = sample(c(0, 1), 1, prob = c(1 - .data$CNSR_P, .data$CNSR_P)), AVAL = stats::rexp(1, .data$LAMBDA), AVALU = \"DAYS\", EVNTDESC = if (.data$CNSR == 1) { sample(evntdescr_sel[-c(1:2)], 1) } else { ifelse(.data$PARAMCD == \"OS\", sample(evntdescr_sel[1], 1), sample(evntdescr_sel[c(1:2)], 1) ) } ) %>% dplyr::select(-\"LAMBDA\", -\"CNSR_P\") }) %>% Reduce(rbind, .) # merge ADSL to be able to add TTE date and study day variables adtte <- dplyr::inner_join( adsl, dplyr::select(adtte, -\"ARM\"), by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::mutate(ADTM = sample( seq(lubridate::as_datetime(TRTSDTM), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1 )) %>% dplyr::select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ADTM) adtte <- adtte %>% dplyr::group_by(.data$USUBJID) %>% dplyr::mutate(PARAM = as.factor(.data$PARAM)) %>% dplyr::mutate(PARAMCD = as.factor(.data$PARAMCD)) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$ADTM ) lbls <- col_labels(adtte) # adding adverse event counts and log follow-up time tmc_ex_adtte <- dplyr::bind_rows( adtte, data.frame(adtte %>% dplyr::group_by(.data$USUBJID) %>% dplyr::slice_head(n = 1) %>% dplyr::mutate( PARAMCD = \"TNE\", PARAM = \"Total Number of Exacerbations\", AVAL = stats::rpois(1, 3), AVALU = \"COUNT\", lgTMATRSK = log(stats::rexp(1, rate = 3)), dplyr::across(c(\"ADTM\", \"EVNTDESC\"), ~NA) )) ) %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$ADTM ) col_labels(tmc_ex_adtte) <- c(lbls, lgTMATRSK = \"Log Time At Risk\") i_lbls <- sapply( names(col_labels(tmc_ex_adtte)[is.na(col_labels(tmc_ex_adtte))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_adtte[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_adtte, file = \"data/tmc_ex_adtte.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"advs","dir":"Articles","previous_headings":"","what":"ADVS","title":"Example Data Generation","text":"","code":"generate_advs <- function(adsl = tmc_ex_adsl, n_assessments = 5L, n_days = 5L) { set.seed(1) param <- c( \"Diastolic Blood Pressure\", \"Pulse Rate\", \"Respiratory Rate\", \"Systolic Blood Pressure\", \"Temperature\", \"Weight\" ) paramcd <- c(\"DIABP\", \"PULSE\", \"RESP\", \"SYSBP\", \"TEMP\", \"WEIGHT\") paramu <- c(\"Pa\", \"beats/min\", \"breaths/min\", \"Pa\", \"C\", \"Kg\") visit_format <- \"WEEK\" param_init_list <- relvar_init(param, paramcd) unit_init_list <- relvar_init(param, paramu) advs <- expand.grid( STUDYID = unique(adsl$STUDYID), USUBJID = adsl$USUBJID, PARAM = as.factor(param_init_list$relvar1), AVISIT = visit_schedule(visit_format = visit_format, n_assessments = n_assessments), stringsAsFactors = FALSE ) advs <- dplyr::mutate( advs, AVISITN = dplyr::case_when( AVISIT == \"SCREENING\" ~ -1, AVISIT == \"BASELINE\" ~ 0, (grepl(\"^WEEK\", AVISIT) | grepl(\"^CYCLE\", AVISIT)) ~ as.numeric(AVISIT) - 2, TRUE ~ NA_real_ ) ) advs$PARAMCD <- as.factor(rel_var( df = advs, var_name = \"PARAMCD\", var_values = param_init_list$relvar2, related_var = \"PARAM\" )) advs$AVALU <- as.factor(rel_var( df = advs, var_name = \"AVALU\", var_values = unit_init_list$relvar2, related_var = \"PARAM\" )) advs$AVAL <- stats::rnorm(nrow(advs), mean = 50, sd = 8) advs <- advs[order(advs$STUDYID, advs$USUBJID, advs$PARAMCD, advs$AVISITN), ] advs <- dplyr::inner_join( adsl, advs, by = c(\"STUDYID\", \"USUBJID\"), multiple = \"all\" ) %>% dplyr::rowwise() %>% dplyr::mutate(TRTENDT = lubridate::date(dplyr::case_when( is.na(TRTEDTM) ~ lubridate::floor_date(lubridate::date(TRTSDTM) + study_duration_secs, unit = \"day\"), TRUE ~ TRTEDTM ))) %>% dplyr::mutate(ADTM = sample( seq(lubridate::as_datetime(TRTSDTM), lubridate::as_datetime(TRTENDT), by = \"day\"), size = 1 )) %>% dplyr::mutate(ADY = ceiling(difftime(ADTM, TRTSDTM, units = \"days\"))) %>% dplyr::select(-TRTENDT) %>% dplyr::ungroup() %>% dplyr::arrange(.data$STUDYID, .data$USUBJID, .data$ADTM) tmc_ex_advs <- advs %>% dplyr::group_by(.data$USUBJID) %>% dplyr::ungroup() %>% dplyr::arrange( .data$STUDYID, .data$USUBJID, .data$PARAMCD, .data$AVISITN, .data$ADTM ) i_lbls <- sapply( names(col_labels(tmc_ex_advs)[is.na(col_labels(tmc_ex_advs))]), function(x) which(names(common_var_labels) == x) ) col_labels(tmc_ex_advs[names(i_lbls)]) <- common_var_labels[i_lbls] save(tmc_ex_advs, file = \"data/tmc_ex_advs.rda\", compress = \"xz\") }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/generate_tmc_test_data.html","id":"generate-data","dir":"Articles","previous_headings":"","what":"Generate Data","title":"Example Data Generation","text":"","code":"# Generate & load adsl tmp_fol <- getwd() setwd(dirname(tmp_fol)) generate_adsl() load(\"data/tmc_ex_adsl.rda\") # Generate other datasets generate_adae() generate_adaette() generate_adcm() generate_adeg() generate_adex() generate_adlb() generate_admh() generate_adqs() generate_adrs() generate_adtte() generate_advs() setwd(tmp_fol)"},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/quickstart_substitute.html","id":"section","dir":"Articles","previous_headings":"","what":"Quick start: `substitute` for NSE","title":"Quick start: `substitute` for NSE","text":"Considering expression, R usually evaluates returns value. Instead focusing value, also possible work code generated value. non standard evaluation, NSE, starts. function substitute important element non-standard evaluation. instance, consider defined <- 5, expression returns 5, substitute() returns code obtain value: . principle teal relies : generate expressions. return result expression result panel app. return corresponding code (expression) Show R Code. expression returning displayed value must reactive. information encoding one hand, filtering panel hand modify expression displayed value. , teal needs work expressions values relies heavily NSE. NSE advanced notion mixing Shiny app development source difficulties : hindered coding efficiency Shiny app must run order check correct execution code. limited possibilities testing. alternative, possible focus first NSE aspects plain R, ready, integrate Shiny App. following practical examples demonstrating NSE works. choice made focus substitute.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/quickstart_substitute.html","id":"nse-principle","dir":"Articles","previous_headings":"The Basics","what":"NSE Principle","title":"Quick start: `substitute` for NSE","text":"happened? substitute returns code value, attempt run code, therefore possible return expression make sense (yet), instance involving two non defined objects. values b exist, expression can run without error: Now, function name substitute reason. returning expression, also operates substitutions terms within given expression. happened? objects b exist function environment substitute called. terms expression within substitute replaced values b. Indeed, returning expression, substitute verifies b don’t value existing evaluation environment. , values b used expression. also possible use second argument substitute, env, environment (list) containing objects. expression submitted substitute corresponding objects env, terms within expression substituted provided values: happened? environment values b taken directly declared within substitute expression (argument expr) values substituted (argument env). substitute returned non-evaluated expression, use eval() evaluate . slightly elaborate expression: Note : x argument name plot preserved, x object replaced.","code":"non_evaluated_expression <- substitute(expr = a + b) non_evaluated_expression ## a + b eval(non_evaluated_expression) ## Error in eval(non_evaluated_expression): object 'b' not found non_evaluated_expression <- substitute(expr = a + b) a <- 1 b <- 5 eval(non_evaluated_expression) ## [1] 6 fun <- function(a, b) { substitute(expr = a + b) } non_evaluated_expression <- fun(5, -2) non_evaluated_expression ## 5 + -2 eval(non_evaluated_expression) ## [1] 3 non_evaluated_expression <- substitute( expr = a + b, env = list(a = 5, b = 5) ) non_evaluated_expression ## 5 + 5 eval(non_evaluated_expression) ## [1] 10 non_evaluated_expression <- substitute( expr = plot(x = x, y = exp(x), main = text), env = list(x = 0:10, text = \"A graph\") ) non_evaluated_expression ## plot(x = 0:10, y = exp(0:10), main = \"A graph\") eval(non_evaluated_expression)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/quickstart_substitute.html","id":"replace-an-object-name","dir":"Articles","previous_headings":"The Basics","what":"Replace an object name","title":"Quick start: `substitute` for NSE","text":"formulas, character strings accepted, execute substitution? object names specific class (name); .names coerces character string object name (alternatively, .symbol provides identical result):","code":"# Error expected: plot_expr <- substitute( expr = plot(y ~ x, data = iris, main = text), env = list( x = Sepal.Length, y = Sepal.Width, text = \"Iris, again ...\" ) ) ## Error: object 'Sepal.Length' not found # Error expected: plot_expr <- substitute( expr = plot(y ~ x, data = iris, main = text), env = list( x = \"Sepal.Length\", y = \"Sepal.Width\", text = \"Iris, again ...\" ) ) plot_expr ## plot(\"Sepal.Width\" ~ \"Sepal.Length\", data = iris, main = \"Iris, again ...\") eval(plot_expr) ## Error in terms.formula(formula, data = data): invalid term in model formula plot_expr <- substitute( expr = plot(y ~ x, data = iris, main = text), env = list( x = as.name(\"Sepal.Length\"), y = as.symbol(\"Sepal.Width\"), text = \"Iris, again ...\" ) ) plot_expr ## plot(Sepal.Width ~ Sepal.Length, data = iris, main = \"Iris, again ...\") eval(plot_expr)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/quickstart_substitute.html","id":"what-about-dataframe-names","dir":"Articles","previous_headings":"The Basics","what":"What about dataframe names?","title":"Quick start: `substitute` for NSE","text":"Lets imagine pipe-flavored expression, df term corresponding dataframe substituted: df %>% plot(y ~ x, data = ., main = text). principle exposed can work directly without addition. However, df expression replaced directly value object provided expression generating dataframe: pipeline working humanly readable. can replace value expression generating value? pretty much topic vignette: substitute.","code":"library(dplyr) ## Error in get(paste0(generic, \".\", class), envir = get_method_env()) : ## object 'type_sum.accel' not found ## ## Attaching package: 'dplyr' ## The following objects are masked from 'package:stats': ## ## filter, lag ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union short_iris <- head(iris) plot_expr <- substitute( expr = df %>% plot(y ~ x, data = ., main = text), env = list( df = short_iris, x = as.name(\"Sepal.Length\"), y = as.symbol(\"Sepal.Width\"), text = \"Iris, again ...\" ) ) eval(plot_expr) plot_expr ## list(Sepal.Length = c(5.1, 4.9, 4.7, 4.6, 5, 5.4), Sepal.Width = c(3.5, ## 3, 3.2, 3.1, 3.6, 3.9), Petal.Length = c(1.4, 1.4, 1.3, 1.5, ## 1.4, 1.7), Petal.Width = c(0.2, 0.2, 0.2, 0.2, 0.2, 0.4), Species = c(1L, ## 1L, 1L, 1L, 1L, 1L)) %>% plot(Sepal.Width ~ Sepal.Length, data = ., ## main = \"Iris, again ...\") plot_expr <- substitute( expr = df %>% plot(y ~ x, data = ., main = text), env = list( df = substitute(iris), x = as.name(\"Sepal.Length\"), y = as.symbol(\"Sepal.Width\"), text = \"Iris, again ...\" ) ) plot_expr ## iris %>% plot(Sepal.Width ~ Sepal.Length, data = ., main = \"Iris, again ...\") eval(plot_expr)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/quickstart_substitute.html","id":"in-a-nutshell","dir":"Articles","previous_headings":"The Basics","what":"In a nutshell","title":"Quick start: `substitute` for NSE","text":"expr expression (eventually) substituted. env environment potential replacement value might needed. object name (like formulas e.g. y ~ x) , use .name .symbol. data frame name (like iris) , use substitute.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/quickstart_substitute.html","id":"direct-use-of-substitute","dir":"Articles","previous_headings":"rtables","what":"Direct use of substitute","title":"Quick start: `substitute` for NSE","text":"substitute approach can used rtables pipelines. Lets prepare example reporting data LB domain. example based template LBT01; target report columns lab test result per study arm, values (AVAL) changes baseline (CHG), per analysis visit rows. data can prepared follows: rtables expression obtained : expression valid … : … easily readable …: … can arranged:","code":"library(teal.modules.clinical) library(dplyr) adlb <- tmc_ex_adlb adlb_f <- adlb %>% filter( PARAM == \"Alanine Aminotransferase Measurement\" & ARMCD %in% c(\"ARM A\", \"ARM B\") & AVISIT == \"WEEK 1 DAY 8\" ) rtables_expr <- substitute( expr = basic_table() %>% split_cols_by(arm, split_fun = drop_split_levels) %>% split_rows_by(visit, split_fun = drop_split_levels) %>% split_cols_by_multivar( vars = c(\"AVAL\", \"CHG\"), varlabels = c(\"Value\", \"Change\") ) %>% summarize_colvars() %>% build_table(df = df), env = list( df = substitute(adlb_f), arm = \"ARM\", visit = \"AVISIT\" ) ) eval(rtables_expr) ## A: Drug X B: Placebo ## Value Change Value Change ## —————————————————————————————————————————————————————————————————————— ## WEEK 1 DAY 8 ## n 69 69 73 73 ## Mean (SD) 20.8 (4.1) 1.6 (6.1) 20.2 (4.1) -0.2 (5.6) ## Median 20.4 2.4 20.0 -0.2 ## Min - Max 12.8 - 34.6 -11.3 - 14.2 12.6 - 29.0 -12.8 - 10.8 rtables_expr ## basic_table() %>% split_cols_by(\"ARM\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISIT\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c(\"Value\", ## \"Change\")) %>% summarize_colvars() %>% build_table(df = adlb_f) library(teal) library(styler) #' Stylish code #' #' Deparse an expression and display the code following NEST conventions. #' #' @param expr (`call`)\\cr or possibly understood as so. #' styled_expr <- function(expr) { print( styler::style_text(text = deparse(expr)), colored = FALSE ) } #' #' @examples styled_expr(rtables_expr) ## basic_table() %>% ## split_cols_by(\"ARM\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISIT\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c( ## \"Value\", ## \"Change\" ## )) %>% ## summarize_colvars() %>% ## build_table(df = adlb_f)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/quickstart_substitute.html","id":"substitute-in-a-function","dir":"Articles","previous_headings":"rtables","what":"substitute in a function","title":"Quick start: `substitute` for NSE","text":"Moving , substitute can actually wrapped function, way rtables pipelines programmatically obtained: results obtained … , fine tuning easier. instance, variable designating study arm visit can changed, expected feature teal module encoding panel.","code":"rtables_expr <- function(df, arm, visit) { substitute( expr = basic_table() %>% split_cols_by(arm, split_fun = drop_split_levels) %>% split_rows_by(visit, split_fun = drop_split_levels) %>% split_cols_by_multivar( vars = c(\"AVAL\", \"CHG\"), varlabels = c(\"Value\", \"Change\") ) %>% summarize_colvars() %>% build_table(df = df), env = list( df = substitute(df), arm = arm, visit = visit ) ) } result <- rtables_expr(df = adlb_f, arm = \"ARM\", visit = \"AVISIT\") styled_expr(result) ## basic_table() %>% ## split_cols_by(\"ARM\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISIT\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c( ## \"Value\", ## \"Change\" ## )) %>% ## summarize_colvars() %>% ## build_table(df = adlb_f) eval(result) ## A: Drug X B: Placebo ## Value Change Value Change ## —————————————————————————————————————————————————————————————————————— ## WEEK 1 DAY 8 ## n 69 69 73 73 ## Mean (SD) 20.8 (4.1) 1.6 (6.1) 20.2 (4.1) -0.2 (5.6) ## Median 20.4 2.4 20.0 -0.2 ## Min - Max 12.8 - 34.6 -11.3 - 14.2 12.6 - 29.0 -12.8 - 10.8 result <- rtables_expr(df = adlb_f, arm = \"ARMCD\", visit = \"AVISITN\") eval(result) ## Split var [AVISITN] was not character or factor. Converting to factor ## ARM A ARM B ## Value Change Value Change ## ————————————————————————————————————————————————————————————————————— ## 1 ## n 69 69 73 73 ## Mean (SD) 20.8 (4.1) 1.6 (6.1) 20.2 (4.1) -0.2 (5.6) ## Median 20.4 2.4 20.0 -0.2 ## Min - Max 12.8 - 34.6 -11.3 - 14.2 12.6 - 29.0 -12.8 - 10.8 styled_expr(result) ## basic_table() %>% ## split_cols_by(\"ARMCD\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISITN\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c( ## \"Value\", ## \"Change\" ## )) %>% ## summarize_colvars() %>% ## build_table(df = adlb_f)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/quickstart_substitute.html","id":"chain-expressions-in-a-pipeline","dir":"Articles","previous_headings":"rtables","what":"Chain expressions in a pipeline","title":"Quick start: `substitute` for NSE","text":"also possible manipulate expressions, instance, expressions might chained pipeline. Expressions can arranged list, way, possible conditional editing expressions. context rtables, layers enclosing analyze call handle .stats option. lean expression include .stats option, default value changed. expected feature teal module rendering code Show R Code: First application standard statistics: statistics specifications:","code":"#' Expressions as a pipeline #' #' Accepts expressions to be chained using the `magrittr` pipeline-flavor. #' @param ... (`call`)\\cr or object which can be interpreted as so. #' (e.g. `name`) #' pipe_expr <- function(...) { exprs <- unlist(list(...)) exprs <- lapply( exprs, function(x) { x <- deparse(x) paste(x, collapse = \" \") } ) exprs <- unlist(exprs) exprs <- paste(exprs, collapse = \" %>% \") str2lang(exprs) } #' @examples result <- pipe_expr( expr1 = substitute(df), expr2 = substitute(head) ) result ## df %>% head rtables_expr <- function(df, arm, visit, .stats = NULL) { # The rtables layout is decomposed into a list of expressions. lyt <- list() # 1. First the columns and rows: lyt$structure <- substitute( expr = basic_table() %>% split_cols_by(arm, split_fun = drop_split_levels) %>% split_rows_by(visit, split_fun = drop_split_levels) %>% split_cols_by_multivar( vars = c(\"AVAL\", \"CHG\"), varlabels = c(\"Value\", \"Change\") ), env = list( arm = arm, visit = visit ) ) # 2. The analyze layer which depends on the use of .stats. lyt$analyze <- if (is.null(.stats)) { substitute( summarize_colvars() ) } else { substitute( summarize_colvars(.stats = .stats), list(.stats = .stats) ) } # 3. And finishing with rtables::build_table. lyt$build <- substitute( build_table(df = df), list(df = substitute(df)) ) # As previously demonstrated, expressions can be manipulated and # chained in a pipeline. pipe_expr(lyt) } result <- rtables_expr(df = adlb_f, arm = \"ARM\", visit = \"AVISIT\") styled_expr(result) ## basic_table() %>% ## split_cols_by(\"ARM\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISIT\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c( ## \"Value\", ## \"Change\" ## )) %>% ## summarize_colvars() %>% ## build_table(df = adlb_f) eval(result) ## A: Drug X B: Placebo ## Value Change Value Change ## —————————————————————————————————————————————————————————————————————— ## WEEK 1 DAY 8 ## n 69 69 73 73 ## Mean (SD) 20.8 (4.1) 1.6 (6.1) 20.2 (4.1) -0.2 (5.6) ## Median 20.4 2.4 20.0 -0.2 ## Min - Max 12.8 - 34.6 -11.3 - 14.2 12.6 - 29.0 -12.8 - 10.8 result <- rtables_expr( df = adlb_f, arm = \"ARM\", visit = \"AVISIT\", .stats = c(\"n\", \"mean_sd\") ) styled_expr(result) ## basic_table() %>% ## split_cols_by(\"ARM\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISIT\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c( ## \"Value\", ## \"Change\" ## )) %>% ## summarize_colvars(.stats = c(\"n\", \"mean_sd\")) %>% ## build_table(df = adlb_f) eval(result) ## A: Drug X B: Placebo ## Value Change Value Change ## ——————————————————————————————————————————————————————————————— ## WEEK 1 DAY 8 ## n 69 69 73 73 ## Mean (SD) 20.8 (4.1) 1.6 (6.1) 20.2 (4.1) -0.2 (5.6)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/quickstart_substitute.html","id":"including-pre-processing","dir":"Articles","previous_headings":"rtables","what":"Including pre-processing","title":"Quick start: `substitute` for NSE","text":"Finally, also possible wrap several expressions single function. instance, teal module generally includes pre-processing section: now possible modify studied parameter (PARAMCD) addition study arm visit variables names. two expressions consistent: two expressions can executed return rtables:","code":"rtables_expr <- function(df, paramcd, arm, visit, .stats = NULL) { # y is a list which will collect two expressions: # 1. y$data with the preprocessing steps. # 2. y$rtables the table layout and build. y <- list() # 1. Preprocessing --- y$data <- substitute( df <- df %>% filter( PARAMCD == paramcd & ARMCD %in% c(\"ARM A\", \"ARM B\") & AVISIT == \"WEEK 1 DAY 8\" ), list( df = substitute(df), paramcd = paramcd ) ) # 2. rtables layout --- lyt <- list() lyt$structure <- substitute( expr = basic_table() %>% split_cols_by(arm, split_fun = drop_split_levels) %>% split_rows_by(visit, split_fun = drop_split_levels) %>% split_cols_by_multivar( vars = c(\"AVAL\", \"CHG\"), varlabels = c(\"Value\", \"Change\") ), env = list( arm = arm, visit = visit ) ) lyt$analyze <- if (is.null(.stats)) { substitute( summarize_colvars() ) } else { substitute( summarize_colvars(.stats = .stats), list(.stats = .stats) ) } lyt$build <- substitute( build_table(df = df), list(df = substitute(df)) ) y$rtables <- pipe_expr(lyt) # Finally returns y as a list with two expressions. y } adlb <- tmc_ex_adlb result <- rtables_expr( df = adlb, paramcd = \"CRP\", arm = \"ARM\", visit = \"AVISIT\", .stats = c(\"n\", \"mean_sd\") ) styled_expr(result$data) ## adlb <- adlb %>% filter(PARAMCD == \"CRP\" & ARMCD %in% c( ## \"ARM A\", ## \"ARM B\" ## ) & AVISIT == \"WEEK 1 DAY 8\") styled_expr(result$rtables) ## basic_table() %>% ## split_cols_by(\"ARM\", split_fun = drop_split_levels) %>% ## split_rows_by(\"AVISIT\", split_fun = drop_split_levels) %>% ## split_cols_by_multivar(vars = c(\"AVAL\", \"CHG\"), varlabels = c( ## \"Value\", ## \"Change\" ## )) %>% ## summarize_colvars(.stats = c(\"n\", \"mean_sd\")) %>% ## build_table(df = adlb) result_exec <- mapply(eval, result) result_exec$rtables ## A: Drug X B: Placebo ## Value Change Value Change ## ———————————————————————————————————————————————————————————— ## WEEK 1 DAY 8 ## n 69 69 73 73 ## Mean (SD) 1.0 (0.2) 0.0 (0.3) 1.0 (0.2) 0.0 (0.3)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/quickstart_substitute.html","id":"in-a-nutshell-1","dir":"Articles","previous_headings":"rtables","what":"In a nutshell","title":"Quick start: `substitute` for NSE","text":"point, possible : generate rtables pipelines. chain expressions pipeline (e.g. pipe_expr) decompose rtables pipeline add conditional layers (e.g. .stats). group expressions single list control pre-processing rtables pipeline.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/teal-modules-clinical.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Getting Started with {teal.modules.clinical}","text":"teal.modules.clinical package implementing number teal modules helpful exploring clinical trials data, specifically targeted towards data following ADaM standards. teal.modules.clinical modules can used data ADaM standard clinical data, features package tailored towards data type. concepts presented require knowledge core features teal, specifically launch teal application pass data . Therefore, highly recommended refer home page introductory vignette teal package.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/teal-modules-clinical.html","id":"main-features","dir":"Articles","previous_headings":"","what":"Main Features","title":"Getting Started with {teal.modules.clinical}","text":"package provides ready--use teal modules can embed teal application. modules generate highly customizable tables, plots, outputs often used exploratory data analysis, including: ANCOVA - tm_t_ancova() Cox regression - tm_t_coxreg() Kaplan-Meier plot - tm_g_km() Logistic regression - tm_t_logistic() Bar chart - tm_g_barchart_simple() Confidence interval plot - tm_g_ci() Binary outcome response table - tm_t_binary_outcome() Summary adverse events table - tm_t_events_summary() SMQ table - tm_t_smq() Time--event table - tm_t_tte() library also offers group patient profile modules targeted clinical statisticians physicians want review data per patient basis. modules present data patient’s adverse events, severity, current therapy, laboratory results . See full index package functions & modules .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/teal-modules-clinical.html","id":"a-simple-application","dir":"Articles","previous_headings":"","what":"A Simple Application","title":"Getting Started with {teal.modules.clinical}","text":"teal.modules.clinical module needs embedded inside shiny/teal application interact . simple application including bar chart module look like :","code":"library(teal.modules.clinical) library(nestcolor) ADSL <- tmc_ex_adsl ADAE <- tmc_ex_adae app <- init( data = cdisc_data( ADSL = ADSL, ADAE = ADAE, code = \" ADSL <- tmc_ex_adsl ADAE <- tmc_ex_adae \" ), modules = list( tm_g_barchart_simple( label = \"ADAE Analysis\", x = data_extract_spec( dataname = \"ADAE\", select = select_spec( choices = variable_choices( ADAE, c( \"ARM\", \"ACTARM\", \"SEX\", \"RACE\", \"SAFFL\", \"STRATA2\" ) ), selected = \"ACTARM\", multiple = FALSE ) ) ) ) ) shinyApp(app$ui, app$server)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/articles/teal-modules-clinical.html","id":"try-it-out-in-shinylive","dir":"Articles","previous_headings":"A Simple Application","what":"Try it out in Shinylive","title":"Getting Started with {teal.modules.clinical}","text":"Open Shinylive Consider consulting documentation examples module (e.g. ?tm_g_barchart_simple). many, can also find useful links TLG Catalog additional example apps can found. teal.modules.clinical exports modules needs support libraries run teal app flesh functionality. example , tm_g_barchart_simple() function teal.modules.clinical whereas init() teal function, data_extract_spec(), select_spec(), variable_choices() teal.transform functions, cdisc_data() teal.data function. Let’s break app pieces: lines load libraries used example. use example data provided teal.modules.clinical package: nestcolor optional package can loaded apply standardized NEST color palette module plots. need load teal teal.modules.clinical already depends . next step, use teal create shiny UI server functions can launch using shiny. data argument tells teal input data - ADaM datasets ADSL ADAE - modules argument indicates modules included application. , include one module: tm_g_barchart_simple(). Finally, use shiny launch application: teal.modules.clinical modules allow specification arguments using teal.transform::choices_selected(), tm_t_summary() module following example. Please refer API reference specific modules examples information customization options available.","code":"library(teal.modules.clinical) library(nestcolor) ADSL <- tmc_ex_adsl ADAE <- tmc_ex_adae app <- init( data = cdisc_data( ADSL = ADSL, ADAE = ADAE, code = \" ADSL <- tmc_ex_adsl ADAE <- tmc_ex_adae \" ), modules = list( tm_g_barchart_simple( label = \"ADAE Analysis\", x = data_extract_spec( dataname = \"ADAE\", select = select_spec( choices = variable_choices( ADAE, c( \"ARM\", \"ACTARM\", \"SEX\", \"RACE\", \"SAFFL\", \"STRATA2\" ) ), selected = \"ACTARM\", multiple = FALSE ) ) ) ) ) if (interactive()) shinyApp(app$ui, app$server) ADSL <- tmc_ex_adsl app <- init( data = cdisc_data(ADSL = ADSL, code = \"ADSL <- tmc_ex_adsl\"), modules = list( tm_t_summary( label = \"Demographic Table\", dataname = \"ADSL\", arm_var = choices_selected(choices = c(\"ARM\", \"ARMCD\"), selected = \"ARM\"), summarize_vars = choices_selected( choices = c(\"SEX\", \"RACE\", \"BMRKR2\", \"EOSDY\", \"DCSREAS\", \"AGE\"), selected = c(\"SEX\", \"RACE\") ) ) ) ) if (interactive()) shinyApp(app$ui, app$server)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Joe Zhu. Author, maintainer. Jana Stoilova. Author. Davide Garolini. Author. Emily de la Rua. Author. Abinaya Yogasekaram. Author. Mahmoud Hallal. Author. Dawid Kaledkowski. Author. Rosemary Li. Author. Heng Wang. Author. Pawel Rucki. Author. Nikolas Burkoff. Author. Konrad Pagacz. Author. Vaakesan Sundrelingam. Contributor. Francois Collin. Contributor. Imanol Zubizarreta. Contributor. F. Hoffmann-La Roche AG. Copyright holder, funder.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Zhu J, Stoilova J, Garolini D, de la Rua E, Yogasekaram , Hallal M, Kaledkowski D, Li R, Wang H, Rucki P, Burkoff N, Pagacz K (2024). teal.modules.clinical: 'teal' Modules Standard Clinical Outputs. R package version 0.9.1.9042, https://github.com/insightsengineering/teal.modules.clinical/, https://insightsengineering.github.io/teal.modules.clinical/main/.","code":"@Manual{, title = {teal.modules.clinical: 'teal' Modules for Standard Clinical Outputs}, author = {Joe Zhu and Jana Stoilova and Davide Garolini and Emily {de la Rua} and Abinaya Yogasekaram and Mahmoud Hallal and Dawid Kaledkowski and Rosemary Li and Heng Wang and Pawel Rucki and Nikolas Burkoff and Konrad Pagacz}, year = {2024}, note = {R package version 0.9.1.9042, https://github.com/insightsengineering/teal.modules.clinical/}, url = {https://insightsengineering.github.io/teal.modules.clinical/main/}, }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/index.html","id":"tealmodulesclinical","dir":"","previous_headings":"","what":"teal Modules for Standard Clinical Outputs","title":"teal Modules for Standard Clinical Outputs","text":"package contains set standard teal modules used CDISC data order generate many standard outputs used clinical trials. modules include, limited : Forest plots (tm_g_forest_rsp()/tm_g_forest_tte()) Line plots (tm_g_lineplot()) Kaplan-Meier plots (tm_g_km()) … MMRM (tm_a_mmrm()) Logistic regression (tm_t_logistic()) Cox regression (tm_t_coxreg()) … Unique patients (tm_t_summary()) Exposure across patients (tm_t_exposure()) Change baseline parameters (tm_t_summary_by()) … Table basic information chosen patient (tm_t_pp_basic_info()) Plot patient vitals time (tm_g_pp_vitals()) General timeline individual patients (tm_g_pp_patient_timeline()) … modules package implemented using functions R package tern order produce output. Please see Teal Gallery TLG Catalog examples shiny apps created using modules package.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"teal Modules for Standard Clinical Outputs","text":"Alternatively, might want use development version.","code":"install.packages('teal.modules.clinical') # install.packages(\"pak\") pak::pak(\"insightsengineering/teal.modules.clinical\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/index.html","id":"usage","dir":"","previous_headings":"","what":"Usage","title":"teal Modules for Standard Clinical Outputs","text":"understand use package, please refer Getting Started article, provides multiple examples code implementation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/index.html","id":"playground","dir":"","previous_headings":"","what":"Playground","title":"teal Modules for Standard Clinical Outputs","text":"can try package without installing Shinylive: stable development","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/index.html","id":"getting-help","dir":"","previous_headings":"","what":"Getting help","title":"teal Modules for Standard Clinical Outputs","text":"encounter bug feature request, please file issue. questions, discussions, staying date, please use teal channel pharmaverse slack workspace.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/index.html","id":"acknowledgment","dir":"","previous_headings":"","what":"Acknowledgment","title":"teal Modules for Standard Clinical Outputs","text":"package result joint efforts many developers stakeholders. like thank everyone contributed far!","code":""},{"path":[]},{"path":[]},{"path":[]},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/add_expr.html","id":null,"dir":"Reference","previous_headings":"","what":"Expression List — add_expr","title":"Expression List — add_expr","text":"Add new expression list (expressions).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/add_expr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Expression List — add_expr","text":"","code":"add_expr(expr_ls, new_expr)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/add_expr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Expression List — add_expr","text":"expr_ls (list call) list new expression added. new_expr (call) new expression add.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/add_expr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Expression List — add_expr","text":"list call.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/add_expr.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Expression List — add_expr","text":"Offers stricter control add new expressions existing list. list expressions can later used generate pipeline, instance pipe_expr.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/add_expr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Expression List — add_expr","text":"","code":"library(rtables) lyt <- list() lyt <- add_expr(lyt, substitute(basic_table())) lyt <- add_expr( lyt, substitute(split_cols_by(var = arm), env = list(armcd = \"ARMCD\")) ) lyt <- add_expr( lyt, substitute( test_proportion_diff( vars = \"rsp\", method = \"cmh\", variables = list(strata = \"strata\") ) ) ) lyt <- add_expr(lyt, quote(build_table(df = dta))) pipe_expr(lyt) #> basic_table() %>% split_cols_by(var = arm) %>% test_proportion_diff(vars = \"rsp\", #> method = \"cmh\", variables = list(strata = \"strata\")) %>% #> build_table(df = dta)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/arm_ref_comp_observer.html","id":null,"dir":"Reference","previous_headings":"","what":"Observer for Treatment reference variable — arm_ref_comp_observer","title":"Observer for Treatment reference variable — arm_ref_comp_observer","text":"Updates reference comparison Treatments selected Treatment variable changes","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/arm_ref_comp_observer.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Observer for Treatment reference variable — arm_ref_comp_observer","text":"","code":"arm_ref_comp_observer( session, input, output, id_ref = \"Ref\", id_comp = \"Comp\", id_arm_var, data, arm_ref_comp, module, on_off = reactive(TRUE), input_id = \"buckets\", output_id = \"arms_buckets\" )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/arm_ref_comp_observer.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Observer for Treatment reference variable — arm_ref_comp_observer","text":"session (environment) shiny session input (character) shiny input output (character) shiny input id_ref (character) id reference Treatment input UI element id_comp (character) id comparison group input UI element id_arm_var (character) id Treatment variable input UI element data (reactive data.frame) dataset used validate Treatment reference inputs set id_ref input. arm_ref_comp (unknown) Treatment reference compare variables provided nested list Treatment variable corresponds list specifying default levels reference comparison treatments. module (character) name module called (used produce informative error messages) on_off (logical) reactive can used stop whole observer FALSE. input_id (character) unique id buckets referenced . output_id (character) name UI id output written .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/arm_ref_comp_observer.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Observer for Treatment reference variable — arm_ref_comp_observer","text":"Returns shinyvalidate::InputValidator checks least one reference comparison arm","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/as_num.html","id":null,"dir":"Reference","previous_headings":"","what":"Parse text input to numeric vector — as_num","title":"Parse text input to numeric vector — as_num","text":"Generic parse text numeric vectors. initially designed robust interpretation text input teal modules.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/as_num.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Parse text input to numeric vector — as_num","text":"","code":"as_num(str) # Default S3 method as_num(str) # S3 method for class 'character' as_num(str) # S3 method for class 'numeric' as_num(str) # S3 method for class 'factor' as_num(str) # S3 method for class 'logical' as_num(str)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/as_num.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Parse text input to numeric vector — as_num","text":"str (vector) extract numeric .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/as_num.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Parse text input to numeric vector — as_num","text":"vector numeric directly parsed numeric boolean. list numeric parsed character string, character string associated list item.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/as_num.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Parse text input to numeric vector — as_num","text":"function intended extract numeric character string, factor levels, boolean return vector numeric.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/as_num.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Parse text input to numeric vector — as_num","text":"","code":"dta <- list( character = c(\"text10,20.5letter30.!\", \"!-.40$$-50e5[\", NA), factor = factor(c(\"]+60e-6, 7.7%%8L\", \"%90sep.100\\\"1L\", NA_character_)), numeric = c(1, -5e+2, NA), logical = c(TRUE, FALSE, NA) ) lapply(dta, as_num) #> $character #> $character[[1]] #> [1] 10.0 20.5 30.0 #> #> $character[[2]] #> [1] -4e-01 -5e+06 #> #> $character[[3]] #> [1] NA #> #> #> $factor #> $factor[[1]] #> [1] 0.00006 7.70000 8.00000 #> #> $factor[[2]] #> [1] 90.0 0.1 1.0 #> #> $factor[[3]] #> [1] NA #> #> #> $numeric #> [1] 1 -500 NA #> #> $logical #> [1] 1 0 NA #>"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/bracket_expr.html","id":null,"dir":"Reference","previous_headings":"","what":"Expressions in Brackets — bracket_expr","title":"Expressions in Brackets — bracket_expr","text":"Groups several expressions single bracketed expression.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/bracket_expr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Expressions in Brackets — bracket_expr","text":"","code":"bracket_expr(exprs)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/bracket_expr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Expressions in Brackets — bracket_expr","text":"exprs (list call) expressions concatenate single bracketed expression.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/bracket_expr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Expressions in Brackets — bracket_expr","text":"{ object. See base::Paren() details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/bracket_expr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Expressions in Brackets — bracket_expr","text":"","code":"adsl <- tmc_ex_adsl adrs <- tmc_ex_adrs expr1 <- substitute( expr = anl <- subset(df, PARAMCD == param), env = list(df = as.name(\"adrs\"), param = \"INVET\") ) expr2 <- substitute(expr = anl$rsp_lab <- d_onco_rsp_label(anl$AVALC)) expr3 <- substitute( expr = { anl$is_rsp <- anl$rsp_lab %in% c(\"Complete Response (CR)\", \"Partial Response (PR)\") } ) res <- bracket_expr(list(expr1, expr2, expr3)) eval(res) table(anl$rsp_lab, anl$is_rsp) #> #> FALSE TRUE #> Complete Response (CR) 0 60 #> Partial Response (PR) 0 45 #> Stable Disease (SD) 50 0 #> Progressive Disease (PD) 39 0 #> Not Evaluable (NE) 6 0"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/call_concatenate.html","id":null,"dir":"Reference","previous_headings":"","what":"Concatenate expressions via a binary operator — call_concatenate","title":"Concatenate expressions via a binary operator — call_concatenate","text":"e.g. combine + ggplot without introducing parentheses due associativity","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/call_concatenate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Concatenate expressions via a binary operator — call_concatenate","text":"","code":"call_concatenate(args, bin_op = \"+\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/call_concatenate.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Concatenate expressions via a binary operator — call_concatenate","text":"args arguments concatenate operator bin_op binary operator concatenate ","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/call_concatenate.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Concatenate expressions via a binary operator — call_concatenate","text":"call","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/call_concatenate.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Concatenate expressions via a binary operator — call_concatenate","text":"","code":"library(ggplot2) # What we want to achieve call(\"+\", quote(f), quote(g)) #> f + g call(\"+\", quote(f), call(\"+\", quote(g), quote(h))) # parentheses not wanted #> f + (g + h) call(\"+\", call(\"+\", quote(f), quote(g)), quote(h)) # as expected without unnecessary parentheses #> f + g + h Reduce(function(existing, new) call(\"+\", existing, new), list(quote(f), quote(g), quote(h))) #> f + g + h # how we do it call_concatenate(list(quote(f), quote(g), quote(h))) #> f + g + h call_concatenate(list(quote(f))) #> f call_concatenate(list()) #> NULL call_concatenate( list(quote(ggplot(mtcars)), quote(geom_point(aes(wt, mpg)))) ) #> ggplot(mtcars) + geom_point(aes(wt, mpg)) eval( call_concatenate( list(quote(ggplot(mtcars)), quote(geom_point(aes(wt, mpg)))) ) )"},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/check_arm_ref_comp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if the Treatment variable is reference or compare — check_arm_ref_comp","text":"","code":"check_arm_ref_comp(x, df_to_check, module)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/check_arm_ref_comp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if the Treatment variable is reference or compare — check_arm_ref_comp","text":"x (character) Name variable df_to_check (data.frame) table check module (character) teal module ref comp called ","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/check_arm_ref_comp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Check if the Treatment variable is reference or compare — check_arm_ref_comp","text":"TRUE FALSE whether variable ref comp","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/clean_description.html","id":null,"dir":"Reference","previous_headings":"","what":"Clean up categorical variable description — clean_description","title":"Clean up categorical variable description — clean_description","text":"Cleaning categorical variable descriptions presenting.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/clean_description.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Clean up categorical variable description — clean_description","text":"","code":"clean_description(x)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/clean_description.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Clean up categorical variable description — clean_description","text":"x (character) vector categories descriptions.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/clean_description.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Clean up categorical variable description — clean_description","text":"string","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/clean_description.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Clean up categorical variable description — clean_description","text":"","code":"clean_description(\"Level A (other text)\") #> [1] \"Level A\" clean_description(\"A long string that should be shortened\") #> [1] \"A long string tha...\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/color_lab_values.html","id":null,"dir":"Reference","previous_headings":"","what":"Mapping function for Laboratory Table — color_lab_values","title":"Mapping function for Laboratory Table — color_lab_values","text":"Map value level characters values proper html tags, colors icons.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/color_lab_values.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Mapping function for Laboratory Table — color_lab_values","text":"","code":"color_lab_values( x, classes = c(\"HIGH\", \"NORMAL\", \"LOW\"), colors = list(HIGH = \"red\", NORMAL = \"grey\", LOW = \"blue\"), default_color = \"black\", icons = list(HIGH = \"glyphicon glyphicon-arrow-up\", LOW = \"glyphicon glyphicon-arrow-down\") )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/color_lab_values.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Mapping function for Laboratory Table — color_lab_values","text":"x (character) vector elements format (value level). classes (character) classes vector. colors (list) color per class. default_color (character) default color. icons (list) certain icons per level.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/color_lab_values.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Mapping function for Laboratory Table — color_lab_values","text":"character vector element formatted HTML tag corresponding value x.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/color_lab_values.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Mapping function for Laboratory Table — color_lab_values","text":"","code":"color_lab_values(c(\"LOW\", \"LOW\", \"HIGH\", \"NORMAL\", \"HIGH\")) #> LOW #> \"LOW<\/i><\/span>\" #> LOW #> \"LOW<\/i><\/span>\" #> HIGH #> \"HIGH<\/i><\/span>\" #> NORMAL #> \"NORMAL<\/i><\/span>\" #> HIGH #> \"HIGH<\/i><\/span>\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/column_annotation_label.html","id":null,"dir":"Reference","previous_headings":"","what":"Get full label, useful for annotating plots — column_annotation_label","title":"Get full label, useful for annotating plots — column_annotation_label","text":"Get full label, useful annotating plots","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/column_annotation_label.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get full label, useful for annotating plots — column_annotation_label","text":"","code":"column_annotation_label(dataset, column, omit_raw_name = FALSE)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/column_annotation_label.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get full label, useful for annotating plots — column_annotation_label","text":"dataset (data.frame) dataset column (character) column get label omit_raw_name (logical) omits raw name square brackets label found","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/column_annotation_label.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get full label, useful for annotating plots — column_annotation_label","text":"\"Label [Column name]\" label exists, otherwise \"Column name\".","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/column_annotation_label.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get full label, useful for annotating plots — column_annotation_label","text":"","code":"data <- mtcars column_annotation_label(data, \"cyl\") #> [1] \"cyl\" attr(data[[\"cyl\"]], \"label\") <- \"Cylinder\" column_annotation_label(data, \"cyl\") #> [1] \"Cylinder [cyl]\" column_annotation_label(data, \"cyl\", omit_raw_name = TRUE) #> [1] \"Cylinder\" column_annotation_label(tmc_ex_adsl, \"ACTARM\") #> [1] \"Description of Actual Arm [ACTARM]\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/control_tte.html","id":null,"dir":"Reference","previous_headings":"","what":"Control Function for Time-To-Event teal Module — control_tte","title":"Control Function for Time-To-Event teal Module — control_tte","text":"Controls arguments Cox regression survival analysis results.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/control_tte.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Control Function for Time-To-Event teal Module — control_tte","text":"","code":"control_tte( surv_time = list(conf_level = 0.95, conf_type = \"plain\", quantiles = c(0.25, 0.75)), coxph = list(pval_method = \"log-rank\", ties = \"efron\", conf_level = 0.95), surv_timepoint = control_surv_timepoint(conf_level = 0.95, conf_type = c(\"plain\", \"none\", \"log\", \"log-log\")) )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/control_tte.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Control Function for Time-To-Event teal Module — control_tte","text":"surv_time (list) control parameters survfit model. See tern::control_surv_time() details. coxph (list) control parameters Cox-PH model. See tern::control_coxph() details. surv_timepoint (list) control parameters survfit model time point. See tern::control_surv_timepoint() details.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_des_filter.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert choices_selected to data_extract_spec with only filter_spec — cs_to_des_filter","title":"Convert choices_selected to data_extract_spec with only filter_spec — cs_to_des_filter","text":"Convert choices_selected data_extract_spec filter_spec","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_des_filter.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert choices_selected to data_extract_spec with only filter_spec — cs_to_des_filter","text":"","code":"cs_to_des_filter( cs, dataname, multiple = FALSE, include_vars = FALSE, label = \"Filter by\" )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_des_filter.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert choices_selected to data_extract_spec with only filter_spec — cs_to_des_filter","text":"cs (choices_selected) object transformed. See teal.transform::choices_selected() details. dataname (character) name data multiple (logical) Whether multiple values shall allowed shiny shiny::selectInput(). include_vars (flag) whether include filter variables fixed selection result. can useful preserving reuse rtables code e.g. label (character) Label print selection field. label, set NULL.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_des_filter.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert choices_selected to data_extract_spec with only filter_spec — cs_to_des_filter","text":"(teal.transform::data_extract_spec())","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_des_select.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert choices_selected to data_extract_spec with only select_spec — cs_to_des_select","title":"Convert choices_selected to data_extract_spec with only select_spec — cs_to_des_select","text":"Convert choices_selected data_extract_spec select_spec","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_des_select.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert choices_selected to data_extract_spec with only select_spec — cs_to_des_select","text":"","code":"cs_to_des_select( cs, dataname, multiple = FALSE, ordered = FALSE, label = \"Select\" )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_des_select.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert choices_selected to data_extract_spec with only select_spec — cs_to_des_select","text":"cs (choices_selected) object transformed. See teal.transform::choices_selected() details. dataname (character) name data multiple (logical) Whether multiple values shall allowed shiny shiny::selectInput(). ordered (logical(1)) Flags whether selection order tracked. label (character) Label print selection field. label, set NULL.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_des_select.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert choices_selected to data_extract_spec with only select_spec — cs_to_des_select","text":"(teal.transform::data_extract_spec())","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_filter_spec.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert choices_selected to filter_spec — cs_to_filter_spec","title":"Convert choices_selected to filter_spec — cs_to_filter_spec","text":"Convert choices_selected filter_spec","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_filter_spec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert choices_selected to filter_spec — cs_to_filter_spec","text":"","code":"cs_to_filter_spec(cs, multiple = FALSE, label = \"Filter by\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_filter_spec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert choices_selected to filter_spec — cs_to_filter_spec","text":"cs (choices_selected) object transformed. See teal.transform::choices_selected() details. multiple (logical) Whether multiple values shall allowed shiny shiny::selectInput(). label (character) Label print selection field. label, set NULL.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_filter_spec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert choices_selected to filter_spec — cs_to_filter_spec","text":"(teal.transform::filter_spec())","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_select_spec.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert choices_selected to select_spec — cs_to_select_spec","title":"Convert choices_selected to select_spec — cs_to_select_spec","text":"Convert choices_selected select_spec","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_select_spec.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert choices_selected to select_spec — cs_to_select_spec","text":"","code":"cs_to_select_spec(cs, multiple = FALSE, ordered = FALSE, label = \"Select\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_select_spec.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert choices_selected to select_spec — cs_to_select_spec","text":"cs (choices_selected) object transformed. See teal.transform::choices_selected() details. multiple (logical) Whether multiple values shall allowed shiny shiny::selectInput(). ordered (logical(1)) Flags whether selection order tracked. label (character) Label print selection field. label, set NULL.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/cs_to_select_spec.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert choices_selected to select_spec — cs_to_select_spec","text":"(select_spec)","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/default_total_label.html","id":null,"dir":"Reference","previous_headings":"","what":"Default string for total column label — default_total_label","title":"Default string for total column label — default_total_label","text":"default string used label \"total\" column. value used default value total_label argument throughout teal.modules.clinical package. specified module user via total_label argument, R environment options via set_default_total_label(), \"Patients\" used.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/default_total_label.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Default string for total column label — default_total_label","text":"","code":"default_total_label() set_default_total_label(total_label)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/default_total_label.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Default string for total column label — default_total_label","text":"total_label (string) Single string value set R environment options default label use \"total\" column. Use getOption(\"tmc_default_total_label\") check current value set R environment (defaults \"Patients\" set).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/default_total_label.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Default string for total column label — default_total_label","text":"default_total_label returns current value R environment option set \"tmc_default_total_label\", \"Patients\" otherwise. set_default_total_label return value.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/default_total_label.html","id":"functions","dir":"Reference","previous_headings":"","what":"Functions","title":"Default string for total column label — default_total_label","text":"default_total_label(): Getter default total column label. set_default_total_label(): Setter default total column label. Sets option \"tmc_default_total_label\" within R environment.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/default_total_label.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Default string for total column label — default_total_label","text":"","code":"# Default settings default_total_label() #> [1] \"All Patients\" getOption(\"tmc_default_total_label\") #> NULL # Set custom value set_default_total_label(\"All Patients\") # Settings after value has been set default_total_label() #> [1] \"All Patients\" getOption(\"tmc_default_total_label\") #> [1] \"All Patients\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/ex_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Simulated CDISC Data for Examples — ex_data","title":"Simulated CDISC Data for Examples — ex_data","text":"Simulated CDISC Data Examples","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/ex_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simulated CDISC Data for Examples — ex_data","text":"","code":"tmc_ex_adsl tmc_ex_adae tmc_ex_adaette tmc_ex_adcm tmc_ex_adeg tmc_ex_adex tmc_ex_adlb tmc_ex_admh tmc_ex_adqs tmc_ex_adrs tmc_ex_adtte tmc_ex_advs"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/ex_data.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Simulated CDISC Data for Examples — ex_data","text":"rds (data.frame) object class tbl_df (inherits tbl, data.frame) 200 rows 26 columns. object class tbl_df (inherits tbl, data.frame) 541 rows 51 columns. object class tbl_df (inherits tbl, data.frame) 1800 rows 35 columns. object class tbl_df (inherits tbl, data.frame) 512 rows 45 columns. object class tbl_df (inherits tbl, data.frame) 5200 rows 48 columns. object class tbl_df (inherits tbl, data.frame) 200 rows 37 columns. object class tbl_df (inherits tbl, data.frame) 3000 rows 58 columns. object class tbl_df (inherits tbl, data.frame) 1077 rows 33 columns. object class tbl_df (inherits tbl, data.frame) 7000 rows 36 columns. object class tbl_df (inherits tbl, data.frame) 1600 rows 34 columns. object class tbl_df (inherits tbl, data.frame) 1000 rows 34 columns. object class tbl_df (inherits tbl, data.frame) 8400 rows 34 columns.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/ex_data.html","id":"functions","dir":"Reference","previous_headings":"","what":"Functions","title":"Simulated CDISC Data for Examples — ex_data","text":"tmc_ex_adsl: ADSL data tmc_ex_adae: ADAE data tmc_ex_adaette: ADAETTE data tmc_ex_adcm: ADCM data tmc_ex_adeg: ADEG data tmc_ex_adex: ADEX data tmc_ex_adlb: ADLB data tmc_ex_admh: ADMH data tmc_ex_adqs: ADQS data tmc_ex_adrs: ADRS data tmc_ex_adtte: ADTTE data tmc_ex_advs: ADVS data","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/extract_input.html","id":null,"dir":"Reference","previous_headings":"","what":"Extracts html id for data_extract_ui — extract_input","title":"Extracts html id for data_extract_ui — extract_input","text":"data_extract_ui located extended html id. use ns(\"original id\") reference, extended specific suffixes.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/extract_input.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extracts html id for data_extract_ui — extract_input","text":"","code":"extract_input(varname, dataname, filter = FALSE)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/extract_input.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extracts html id for data_extract_ui — extract_input","text":"varname (character) original html id. retrieved ns(\"original id\") UI function session$ns(\"original id\")/\"original id\" server function. dataname (character)dataname data_extract input. might retrieved like data_extract_spec(...)[[1]]$dataname. filter (logical) optional, connected extract_data_spec objects passed filter argument","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/extract_input.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extracts html id for data_extract_ui — extract_input","text":"string","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/extract_input.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extracts html id for data_extract_ui — extract_input","text":"","code":"extract_input(\"ARM\", \"ADSL\") #> [1] \"ARM-dataset_ADSL_singleextract-select\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/facet_grid_formula.html","id":null,"dir":"Reference","previous_headings":"","what":"Facetting formula x_facet ~ y_facet — facet_grid_formula","title":"Facetting formula x_facet ~ y_facet — facet_grid_formula","text":"Replaces x_facet y_facet . empty character","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/facet_grid_formula.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Facetting formula x_facet ~ y_facet — facet_grid_formula","text":"","code":"facet_grid_formula(x_facet, y_facet)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/facet_grid_formula.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Facetting formula x_facet ~ y_facet — facet_grid_formula","text":"x_facet (character(1)) name x facet, empty, facet along x. y_facet (character(1)) name y facet, empty, facet along y.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/facet_grid_formula.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Facetting formula x_facet ~ y_facet — facet_grid_formula","text":"facet grid formula formula(x_facet ~ y_facet)","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/get_g_forest_obj_var_name.html","id":null,"dir":"Reference","previous_headings":"","what":"Utility function for extracting paramcd for forest plots — get_g_forest_obj_var_name","title":"Utility function for extracting paramcd for forest plots — get_g_forest_obj_var_name","text":"Utility function extracting paramcd forest plots","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/get_g_forest_obj_var_name.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Utility function for extracting paramcd for forest plots — get_g_forest_obj_var_name","text":"","code":"get_g_forest_obj_var_name(paramcd, input, filter_idx = 1)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/get_g_forest_obj_var_name.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Utility function for extracting paramcd for forest plots — get_g_forest_obj_var_name","text":"paramcd teal.transform::data_extract_spec() variable value designating studied parameter. input shiny app input filter_idx filter section index (default 1)","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/get_paramcd_label.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract the associated parameter value for paramcd — get_paramcd_label","title":"Extract the associated parameter value for paramcd — get_paramcd_label","text":"Utility function extracting parameter value associated paramcd value label. parameter value paramcd label, paramcd value returned. used generating title.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/get_paramcd_label.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract the associated parameter value for paramcd — get_paramcd_label","text":"","code":"get_paramcd_label(anl, paramcd)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/get_paramcd_label.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract the associated parameter value for paramcd — get_paramcd_label","text":"anl Analysis dataset paramcd teal.transform::data_extract_spec() variable value designating studied parameter.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/get_var_labels.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get variable labels — get_var_labels","text":"","code":"get_var_labels(datasets, dataname, vars)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/get_var_labels.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get variable labels — get_var_labels","text":"datasets (teal::FilteredData) Data built teal dataname (character) name dataset vars (character) Column names data","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/get_var_labels.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get variable labels — get_var_labels","text":"character variable labels.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/h_concat_expr.html","id":null,"dir":"Reference","previous_headings":"","what":"Expression Deparsing — h_concat_expr","title":"Expression Deparsing — h_concat_expr","text":"Deparse expression string.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/h_concat_expr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Expression Deparsing — h_concat_expr","text":"","code":"h_concat_expr(expr)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/h_concat_expr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Expression Deparsing — h_concat_expr","text":"expr (call) object can used .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/h_concat_expr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Expression Deparsing — h_concat_expr","text":"string.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/h_concat_expr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Expression Deparsing — h_concat_expr","text":"","code":"expr <- quote({ library(rtables) basic_table() %>% split_cols_by(var = \"ARMCD\") %>% test_proportion_diff( vars = \"rsp\", method = \"cmh\", variables = list(strata = \"strata\") ) %>% build_table(df = dta) }) h_concat_expr(expr) #> [1] \"{\\n library(rtables)\\n basic_table() %>% split_cols_by(var = \\\"ARMCD\\\") %>% test_proportion_diff(vars = \\\"rsp\\\", \\n method = \\\"cmh\\\", variables = list(strata = \\\"strata\\\")) %>% \\n build_table(df = dta)\\n}\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/is.cs_or_des.html","id":null,"dir":"Reference","previous_headings":"","what":"Whether object is of class teal.transform::choices_selected() — is.cs_or_des","title":"Whether object is of class teal.transform::choices_selected() — is.cs_or_des","text":"Whether object class teal.transform::choices_selected()","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/is.cs_or_des.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Whether object is of class teal.transform::choices_selected() — is.cs_or_des","text":"","code":"is.cs_or_des(x)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/is.cs_or_des.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Whether object is of class teal.transform::choices_selected() — is.cs_or_des","text":"x object checked","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/is.cs_or_des.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Whether object is of class teal.transform::choices_selected() — is.cs_or_des","text":"(logical)","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/make_barchart_simple_call.html","id":null,"dir":"Reference","previous_headings":"","what":"ggplot2 call to generate simple bar chart — make_barchart_simple_call","title":"ggplot2 call to generate simple bar chart — make_barchart_simple_call","text":"ggplot2 call generate simple bar chart","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/make_barchart_simple_call.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"ggplot2 call to generate simple bar chart — make_barchart_simple_call","text":"","code":"make_barchart_simple_call( y_name, x_name = NULL, fill_name = NULL, x_facet_name = NULL, y_facet_name = NULL, label_bars = TRUE, barlayout = c(\"side_by_side\", \"stacked\"), flip_axis = FALSE, rotate_bar_labels = FALSE, rotate_x_label = FALSE, rotate_y_label = FALSE, expand_y_range = 0, facet_scales = \"free_x\", ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/make_barchart_simple_call.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"ggplot2 call to generate simple bar chart — make_barchart_simple_call","text":"y_name (character NULL) name y-axis variable. x_name (character NULL) name x-axis variable. Defaults NULL dependent extract input can empty. fill_name (character NULL) name variable determine bar fill color. x_facet_name (character NULL) name variable use horizontal plot faceting. y_facet_name (character NULL) name variable use vertical plot faceting. label_bars (logical NULL) whether bars labeled. TRUE, label bar numbers also drawn text. barlayout (character NULL) type bar layout. Options \"stacked\" (default) \"side_by_side\". flip_axis (character NULL) whether flip plot axis. rotate_bar_labels (logical NULL) whether bar labels rotated 45 degrees. rotate_x_label (logical NULL) whether x-axis labels rotated 45 degrees. rotate_y_label (logical NULL) whether y-axis labels rotated 45 degrees. expand_y_range (numeric NULL) fraction y-axis range expand . facet_scales (character) value passed scales argument ggplot2::facet_grid(). Options fixed, free_x, free_y, free. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/make_barchart_simple_call.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"ggplot2 call to generate simple bar chart — make_barchart_simple_call","text":"call produce ggplot object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/module_arguments.html","id":null,"dir":"Reference","previous_headings":"","what":"Standard Module Arguments — module_arguments","title":"Standard Module Arguments — module_arguments","text":"documentation function lists arguments teal modules used repeatedly express analysis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/module_arguments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standard Module Arguments — module_arguments","text":"arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. atirel (teal.transform::choices_selected()) object available choices preselected option ATIREL variable dataname. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. avalu_var (teal.transform::choices_selected()) object available choices preselected option analysis unit variable. avisit (teal.transform::choices_selected()) value analysis visit AVISIT interest. baseline_var (teal.transform::choices_selected()) object available choices preselected option variable values can used baseline_var. by_vars (teal.transform::choices_selected()) object available choices preselected option variable names used split summary rows. cmdecod (teal.transform::choices_selected()) object available choices preselected option CMDECOD variable dataname. cmindc (teal.transform::choices_selected()) object available choices preselected option CMINDC variable dataname. cmstdy (teal.transform::choices_selected()) object available choices preselected option CMSTDY variable dataname. cnsr_var (teal.transform::choices_selected()) object available choices preselected option censoring variable. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). cov_var (teal.transform::choices_selected()) object available choices preselected option covariates variables. dataname (character) analysis data used teal module. default_responses (list character) defines default codes response variable module per value paramcd. passed vector transmitted paramcd values. passed list must named contain arrays, name corresponding single value paramcd. array may contain default response values named arrays rsp default selected response values levels default level choices. fixed_symbol_size (logical) (TRUE), symbol size used plotting estimate. Otherwise, symbol size proportional sample size subgroup. font_size (numeric) numeric vector length 3 current, minimum maximum font size values. hlt (teal.transform::choices_selected()) name variable high level term events. id_var (teal.transform::choices_selected()) object specifying variable name subject id. interact_var (character) name variable interactions arm. interaction needed, default option NULL. interact_y (character) selected item interact_var column used select specific ANCOVA results interact_var discrete. interaction needed, default option FALSE. label (character) menu item label module teal app. llt (teal.transform::choices_selected()) name variable low level term events. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. pre_output (shiny.tag) optional, text placed output put output context. example title. strata_var (teal.transform::choices_selected()) names variables stratified analysis. summarize_vars (teal.transform::choices_selected()) names variables summarized. subgroup_var (teal.transform::choices_selected()) object available choices preselected option variable names can used default subgroups. time_points (teal.transform::choices_selected()) object available choices preselected option time points can used tern::surv_timepoint(). time_unit_var (teal.transform::choices_selected()) object available choices pre-selected option time unit variable. treatment_flag (teal.transform::choices_selected()) value indicating treatment records treatment_flag_var. treatment_flag_var (teal.transform::choices_selected()) treatment flag variable. useNA (character) whether missing data (NA) displayed level. visit_var (teal.transform::choices_selected()) object available choices preselected option variable names can used visit variable. Must factor dataname. worst_flag_indicator (teal.transform::choices_selected()) value indicating worst grade. worst_flag_var (teal.transform::choices_selected()) object available choices preselected option variable names can used worst flag variable. decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/module_arguments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standard Module Arguments — module_arguments","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/module_arguments.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Standard Module Arguments — module_arguments","text":"Although function just returns NULL two uses, teal module users provides documentation arguments commonly consistently used framework. developer adds single reference point import roxygen argument description : @inheritParams module_arguments Parameters identical descriptions & input types Standard Template Arguments section excluded reduce duplication module function inherits parameters corresponding template function.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/normalize_decorators.html","id":null,"dir":"Reference","previous_headings":"","what":"Convert flat list of teal_transform_module to named lists — normalize_decorators","title":"Convert flat list of teal_transform_module to named lists — normalize_decorators","text":"Convert flat list teal_transform_module named lists","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/normalize_decorators.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Convert flat list of teal_transform_module to named lists — normalize_decorators","text":"","code":"normalize_decorators(decorators)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/normalize_decorators.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Convert flat list of teal_transform_module to named lists — normalize_decorators","text":"decorators (list teal_transformodules) normalize.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/normalize_decorators.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Convert flat list of teal_transform_module to named lists — normalize_decorators","text":"named list lists teal_transform_module objects.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/pipe_expr.html","id":null,"dir":"Reference","previous_headings":"","what":"Expressions as a Pipeline — pipe_expr","title":"Expressions as a Pipeline — pipe_expr","text":"Concatenate expressions single pipeline-flavor expression.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/pipe_expr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Expressions as a Pipeline — pipe_expr","text":"","code":"pipe_expr(exprs, pipe_str = \"%>%\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/pipe_expr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Expressions as a Pipeline — pipe_expr","text":"exprs (list call) expressions concatenate pipeline (%>%). pipe_str (character) character separates expressions.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/pipe_expr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Expressions as a Pipeline — pipe_expr","text":"call","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/pipe_expr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Expressions as a Pipeline — pipe_expr","text":"","code":"pipe_expr( list( expr1 = substitute(df), expr2 = substitute(head) ) ) #> df %>% head"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/prepare_arm.html","id":null,"dir":"Reference","previous_headings":"","what":"Expression: Arm Preparation — prepare_arm","title":"Expression: Arm Preparation — prepare_arm","text":"function generate standard expression pre-processing dataset teal module applications. especially interest preprocessing steps needs applied similarly several datasets (e.g. ADSL ADRS).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/prepare_arm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Expression: Arm Preparation — prepare_arm","text":"","code":"prepare_arm( dataname, arm_var, ref_arm, comp_arm, compare_arm = !is.null(ref_arm), ref_arm_val = paste(ref_arm, collapse = \"/\"), drop = TRUE )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/prepare_arm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Expression: Arm Preparation — prepare_arm","text":"dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. compare_arm (logical) triggers comparison study arms. ref_arm_val (character) replacement name reference level. drop (logical) drop unused variable levels.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/prepare_arm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Expression: Arm Preparation — prepare_arm","text":"call","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/prepare_arm.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Expression: Arm Preparation — prepare_arm","text":"teal.modules.clinical, user interface includes manipulation study arms. Classically: arm variable (e.g. ARM, ACTARM), reference arm (0 ), comparison arm (1 ) possibility combine comparison arms. Note arms compared , produced expression reduced optionally dropping non-represented levels arm. comparing arms, pre-processing includes three steps: Filtering dataset retain arms interest (reference comparison). Optional, one arm designated reference combined single level. reference explicitly reassigned non-represented levels arm dropped.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/prepare_arm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Expression: Arm Preparation — prepare_arm","text":"","code":"prepare_arm( dataname = \"adrs\", arm_var = \"ARMCD\", ref_arm = \"ARM A\", comp_arm = c(\"ARM B\", \"ARM C\") ) #> adrs %>% dplyr::filter(ARMCD %in% c(\"ARM A\", \"ARM B\", \"ARM C\")) %>% #> dplyr::mutate(ARMCD = stats::relevel(ARMCD, ref = \"ARM A\")) %>% #> dplyr::mutate(ARMCD = droplevels(ARMCD)) prepare_arm( dataname = \"adsl\", arm_var = \"ARMCD\", ref_arm = c(\"ARM B\", \"ARM C\"), comp_arm = \"ARM A\" ) #> adsl %>% dplyr::filter(ARMCD %in% c(\"ARM B\", \"ARM C\", \"ARM A\")) %>% #> dplyr::mutate(ARMCD = combine_levels(ARMCD, levels = c(\"ARM B\", #> \"ARM C\"), new_level = \"ARM B/ARM C\")) %>% dplyr::mutate(ARMCD = stats::relevel(ARMCD, #> ref = \"ARM B/ARM C\")) %>% dplyr::mutate(ARMCD = droplevels(ARMCD))"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/prepare_arm_levels.html","id":null,"dir":"Reference","previous_headings":"","what":"Expression: Prepare Arm Levels — prepare_arm_levels","title":"Expression: Prepare Arm Levels — prepare_arm_levels","text":"function generates standard expression pre-processing dataset arm levels used apply steps safety teal modules.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/prepare_arm_levels.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Expression: Prepare Arm Levels — prepare_arm_levels","text":"","code":"prepare_arm_levels(dataname, parentname, arm_var, drop_arm_levels = TRUE)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/prepare_arm_levels.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Expression: Prepare Arm Levels — prepare_arm_levels","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/prepare_arm_levels.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Expression: Prepare Arm Levels — prepare_arm_levels","text":"{ object. See base::Paren() details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/prepare_arm_levels.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Expression: Prepare Arm Levels — prepare_arm_levels","text":"","code":"prepare_arm_levels( dataname = \"adae\", parentname = \"adsl\", arm_var = \"ARMCD\", drop_arm_levels = TRUE ) #> { #> adae <- adae %>% dplyr::mutate(ARMCD = droplevels(ARMCD)) #> arm_levels <- levels(adae[[\"ARMCD\"]]) #> adsl <- adsl %>% dplyr::filter(ARMCD %in% arm_levels) #> adsl <- adsl %>% dplyr::mutate(ARMCD = droplevels(ARMCD)) #> } prepare_arm_levels( dataname = \"adae\", parentname = \"adsl\", arm_var = \"ARMCD\", drop_arm_levels = FALSE ) #> { #> adsl <- adsl %>% dplyr::mutate(ARMCD = droplevels(ARMCD)) #> arm_levels <- levels(adsl[[\"ARMCD\"]]) #> adae <- adae %>% dplyr::mutate(ARMCD = factor(ARMCD, levels = arm_levels)) #> }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/select_decorators.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset decorators based on the scope — select_decorators","title":"Subset decorators based on the scope — select_decorators","text":"default protected decorator name always included output, exists","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/select_decorators.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Subset decorators based on the scope — select_decorators","text":"","code":"select_decorators(decorators, scope)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/select_decorators.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Subset decorators based on the scope — select_decorators","text":"decorators (named list) list decorators subset. scope (character) character vector decorator names include.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/select_decorators.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Subset decorators based on the scope — select_decorators","text":"flat list decorators include. can empty list none scope exists decorators argument.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_choices.html","id":null,"dir":"Reference","previous_headings":"","what":"Split choices_selected objects with interactions into their component variables — split_choices","title":"Split choices_selected objects with interactions into their component variables — split_choices","text":"Split choices_selected objects interactions component variables","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_choices.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split choices_selected objects with interactions into their component variables — split_choices","text":"","code":"split_choices(x)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_choices.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split choices_selected objects with interactions into their component variables — split_choices","text":"x (choices_selected) object interaction terms","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_choices.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split choices_selected objects with interactions into their component variables — split_choices","text":"teal.transform::choices_selected() object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_choices.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Split choices_selected objects with interactions into their component variables — split_choices","text":"uses regex \\\\*|: perform split.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_choices.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split choices_selected objects with interactions into their component variables — split_choices","text":"","code":"split_choices(choices_selected(choices = c(\"x:y\", \"a*b\"), selected = all_choices())) #> $choices #> [1] \"x\" \"y\" \"a\" \"b\" #> #> $selected #> [1] \"x\" \"y\" \"a\" \"b\" #> #> $fixed #> [1] FALSE #> #> attr(,\"class\") #> [1] \"choices_selected\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_col_expr.html","id":null,"dir":"Reference","previous_headings":"","what":"Split-Column Expression — split_col_expr","title":"Split-Column Expression — split_col_expr","text":"Renders expression column split rtables depending : expected arm comparison expected arm combination","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_col_expr.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split-Column Expression — split_col_expr","text":"","code":"split_col_expr(compare, combine, ref, arm_var)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_col_expr.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split-Column Expression — split_col_expr","text":"compare (logical) TRUE reference level included. combine (logical) TRUE group combination included. ref (character) reference level (used combine = TRUE). arm_var (character) arm grouping variable name.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_col_expr.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split-Column Expression — split_col_expr","text":"call","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_col_expr.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split-Column Expression — split_col_expr","text":"","code":"split_col_expr( compare = TRUE, combine = FALSE, ref = \"ARM A\", arm_var = \"ARMCD\" ) #> rtables::split_cols_by(var = \"ARMCD\", ref_group = \"ARM A\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_interactions.html","id":null,"dir":"Reference","previous_headings":"","what":"Split interaction terms into their component variables — split_interactions","title":"Split interaction terms into their component variables — split_interactions","text":"Split interaction terms component variables","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_interactions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Split interaction terms into their component variables — split_interactions","text":"","code":"split_interactions(x, by = \"\\\\*|:\")"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_interactions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Split interaction terms into their component variables — split_interactions","text":"x (character) string representing interaction usually form x:y x*y. (character) regex split interaction term .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_interactions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Split interaction terms into their component variables — split_interactions","text":"vector strings element component variable extracted interaction term x.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/split_interactions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Split interaction terms into their component variables — split_interactions","text":"","code":"split_interactions(\"x:y\") #> [1] \"x\" \"y\" split_interactions(\"x*y\") #> [1] \"x\" \"y\""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/srv_decorate_teal_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrappers around srv_transform_teal_data that allows to decorate the data — srv_decorate_teal_data","title":"Wrappers around srv_transform_teal_data that allows to decorate the data — srv_decorate_teal_data","text":"Wrappers around srv_transform_teal_data allows decorate data","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/srv_decorate_teal_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrappers around srv_transform_teal_data that allows to decorate the data — srv_decorate_teal_data","text":"","code":"srv_decorate_teal_data(id, data, decorators, expr, expr_is_reactive = FALSE) ui_decorate_teal_data(id, decorators, ...)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/srv_decorate_teal_data.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrappers around srv_transform_teal_data that allows to decorate the data — srv_decorate_teal_data","text":"id (character(1)) Module id data (reactive teal_data) expr (expression reactive) evaluate output decoration. expression must inline code. See within() Default NULL evaluate appending code. expr_is_reactive (logical(1)) whether expr reactive expression skips defusing argument.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/srv_decorate_teal_data.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Wrappers around srv_transform_teal_data that allows to decorate the data — srv_decorate_teal_data","text":"srv_decorate_teal_data wrapper around srv_transform_teal_data allows decorate data additional expressions. original teal_data object error state, show error first. ui_decorate_teal_data wrapper around ui_transform_teal_data.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/substitute_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Substitute Names in a Quoted Expression — substitute_names","title":"Substitute Names in a Quoted Expression — substitute_names","text":"function substitutes names left- right-hand sides quoted expression. addition can also standard substitutions right-hand side.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/substitute_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Substitute Names in a Quoted Expression — substitute_names","text":"","code":"substitute_names(expr, names, others = list()) h_subst_lhs_names(qexpr, names) substitute_lhs_names(qexpr, names) substitute_rhs(qexpr, env)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/substitute_names.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Substitute Names in a Quoted Expression — substitute_names","text":"expr (language) expression. names (named list name) requested name substitutions. others (named list) requested substitutions happen right-hand side. qexpr (language) quoted expression. env (environment list) requested variable substitutions.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/substitute_names.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Substitute Names in a Quoted Expression — substitute_names","text":"modified expression.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/substitute_names.html","id":"functions","dir":"Reference","previous_headings":"","what":"Functions","title":"Substitute Names in a Quoted Expression — substitute_names","text":"h_subst_lhs_names(): Helper function just substitute top-level names left-hand side quoted expression. substitute_lhs_names(): recursively substitutes names left-hand sides quoted expression. substitute_rhs(): substitutes right-hand side quoted expression. Note just synonym substitute_q().","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/substitute_q.html","id":null,"dir":"Reference","previous_headings":"","what":"Substitute in Quoted Expressions — substitute_q","title":"Substitute in Quoted Expressions — substitute_q","text":"version substitute needed substitute() evaluate first argument, often useful able modify quoted expression.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/substitute_q.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Substitute in Quoted Expressions — substitute_q","text":"","code":"substitute_q(qexpr, env)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/substitute_q.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Substitute in Quoted Expressions — substitute_q","text":"qexpr (language) quoted expression. env (environment list) requested variable substitutions.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/substitute_q.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Substitute in Quoted Expressions — substitute_q","text":"modified expression.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/substitute_q.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Substitute in Quoted Expressions — substitute_q","text":"simplified package pryr avoid another dependency.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/teal.modules.clinical-package.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Modules for Standard Clinical Outputs — teal.modules.clinical-package","title":"teal Modules for Standard Clinical Outputs — teal.modules.clinical-package","text":"Provides teal modules standard clinical trials outputs. teal modules add encoding panel interactively change encodings within teal.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/teal.modules.clinical-package.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"teal Modules for Standard Clinical Outputs — teal.modules.clinical-package","text":"Maintainer: Joe Zhu joe.zhu@roche.com Authors: Jana Stoilova jana.stoilova@roche.com Davide Garolini davide.garolini@roche.com Emily de la Rua emily.de_la_rua@contractors.roche.com Abinaya Yogasekaram abinaya.yogasekaram@contractors.roche.com Mahmoud Hallal mahmoud.hallal@roche.com Dawid Kaledkowski dawid.kaledkowski@roche.com Rosemary Li li.yaqiong@gene.com Heng Wang wang.heng@gene.com Pawel Rucki pawel.rucki@roche.com Nikolas Burkoff Konrad Pagacz contributors: Vaakesan Sundrelingam [contributor] Francois Collin [contributor] Imanol Zubizarreta [contributor] F. Hoffmann-La Roche AG [copyright holder, funder]","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_a_gee.html","id":null,"dir":"Reference","previous_headings":"","what":"Template for Generalized Estimating Equations (GEE) analysis module — template_a_gee","title":"Template for Generalized Estimating Equations (GEE) analysis module — template_a_gee","text":"Creates valid expression generate analysis table using Generalized Estimating Equations (GEE).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_a_gee.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template for Generalized Estimating Equations (GEE) analysis module — template_a_gee","text":"","code":"template_a_gee( output_table, data_model_fit = \"ANL\", dataname_lsmeans = \"ANL_ADSL\", input_arm_var = \"ARM\", ref_group = \"A: Drug X\", aval_var, id_var, arm_var, visit_var, split_covariates, cor_struct, conf_level = 0.95, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_a_gee.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template for Generalized Estimating Equations (GEE) analysis module — template_a_gee","text":"output_table (character) type output table (\"t_gee_cov\", \"t_gee_coef\", \"t_gee_lsmeans\"). data_model_fit (character) dataset used fit model tern.gee::fit_gee(). dataname_lsmeans (character) dataset used alt_counts_df argument rtables::build_table(). aval_var (character) name analysis value variable. id_var (character) variable name subject id. arm_var (character) variable names can used arm_var. visit_var (character) variable names can used visit variable. Must factor dataname. split_covariates (character) vector names variables use covariates tern.gee::vars_gee(). cor_struct (character) assumed correlation structure tern.gee::fit_gee. conf_level (numeric) value confidence level within range (0, 1). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_a_gee.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template for Generalized Estimating Equations (GEE) analysis module — template_a_gee","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_abnormality.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Abnormality Summary Table — template_abnormality","title":"Template: Abnormality Summary Table — template_abnormality","text":"Creates valid expression generate table summarize abnormality.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_abnormality.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Abnormality Summary Table — template_abnormality","text":"","code":"template_abnormality( parentname, dataname, arm_var, id_var = \"USUBJID\", by_vars, abnormal = list(low = c(\"LOW\", \"LOW LOW\"), high = c(\"HIGH\", \"HIGH HIGH\")), grade = \"ANRIND\", baseline_var = \"BNRIND\", treatment_flag_var = \"ONTRTFL\", treatment_flag = \"Y\", add_total = FALSE, total_label = default_total_label(), exclude_base_abn = FALSE, drop_arm_levels = TRUE, na_level = default_na_str(), basic_table_args = teal.widgets::basic_table_args(), tbl_title )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_abnormality.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Abnormality Summary Table — template_abnormality","text":"parentname (character) parent analysis data used teal module, usually refers ADSL. dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. id_var (character) variable name subject id. by_vars (character) variable names used split summary rows. abnormal (named list) indicating abnormality direction grades. grade (character) name variable used specify abnormality grade. Variable must factor. baseline_var (character) name variable specifying baseline abnormality grade. treatment_flag_var (character) name treatment flag variable. treatment_flag (character) name value indicating treatment records treatment_flag_var. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). exclude_base_abn (logical) whether exclude patients abnormal values baseline. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. na_level (character) NA level input dataset, defaults \"\". basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). tbl_title (character) Title label variables bars","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_abnormality.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Abnormality Summary Table — template_abnormality","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_abnormality_by_worst_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Laboratory test results with highest grade post-baseline — template_abnormality_by_worst_grade","title":"Template: Laboratory test results with highest grade post-baseline — template_abnormality_by_worst_grade","text":"Creates valid expression generate table summarize abnormality grade.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_abnormality_by_worst_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Laboratory test results with highest grade post-baseline — template_abnormality_by_worst_grade","text":"","code":"template_abnormality_by_worst_grade( parentname, dataname, arm_var, id_var = \"USUBJID\", paramcd = \"PARAMCD\", atoxgr_var = \"ATOXGR\", worst_high_flag_var = \"WGRHIFL\", worst_low_flag_var = \"WGRLOFL\", worst_flag_indicator = \"Y\", add_total = FALSE, total_label = default_total_label(), drop_arm_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_abnormality_by_worst_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Laboratory test results with highest grade post-baseline — template_abnormality_by_worst_grade","text":"parentname (character) parent analysis data used teal module, usually refers ADSL. dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. id_var (character) variable name subject id. paramcd (character) name parameter code variable. atoxgr_var (character) name variable indicating Analysis Toxicity Grade. worst_high_flag_var (character) name variable indicating Worst High Grade flag worst_low_flag_var (character) name variable indicating Worst Low Grade flag worst_flag_indicator (character) flag value indicating worst grade. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_abnormality_by_worst_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Laboratory test results with highest grade post-baseline — template_abnormality_by_worst_grade","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_adverse_events.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Adverse Events Table and Plot — template_adverse_events","title":"Template: Patient Profile Adverse Events Table and Plot — template_adverse_events","text":"Creates valid expression generate adverse events table ggplot2::ggplot() plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_adverse_events.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Adverse Events Table and Plot — template_adverse_events","text":"","code":"template_adverse_events( dataname = \"ANL\", aeterm = \"AETERM\", tox_grade = \"AETOXGR\", causality = \"AEREL\", outcome = \"AEOUT\", action = \"AEACN\", time = \"ASTDY\", decod = NULL, patient_id, font_size = 12L, ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_adverse_events.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Adverse Events Table and Plot — template_adverse_events","text":"dataname (character) analysis data used teal module. aeterm (character) name reported term adverse event variable. tox_grade (character) name standard toxicity grade variable. causality (character) name causality variable. outcome (character) name outcome adverse event variable. action (character) name action taken study treatment variable. time (character) name study day start adverse event variable. decod (character) name dictionary derived term variable. patient_id (character) patient ID. font_size (numeric) font size value. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_adverse_events.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Adverse Events Table and Plot — template_adverse_events","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_ancova.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: ANCOVA Summary — template_ancova","title":"Template: ANCOVA Summary — template_ancova","text":"Creates valid expression generate analysis variance summary table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_ancova.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: ANCOVA Summary — template_ancova","text":"","code":"template_ancova( dataname = \"ANL\", parentname = \"ADSL\", arm_var, ref_arm = NULL, comp_arm = NULL, combine_comp_arms = FALSE, aval_var, label_aval = NULL, cov_var, include_interact = FALSE, interact_var = NULL, interact_y = FALSE, paramcd_levels = \"\", paramcd_var = \"PARAMCD\", label_paramcd = NULL, visit_levels = \"\", visit_var = \"AVISIT\", conf_level = 0.95, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_ancova.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: ANCOVA Summary — template_ancova","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. combine_comp_arms (logical) triggers combination comparison arms. aval_var (character) name analysis value variable. label_aval (character) label value variable used title rendering. cov_var (character) names covariates variables. include_interact (logical) whether interaction term included model. interact_var (character) name variable interactions arm. interaction needed, default option NULL. interact_y (character) selected item interact_var column used select specific ANCOVA results. interaction needed, default option FALSE. paramcd_levels (character) variable levels studied parameter. paramcd_var (character) variable name studied parameter. label_paramcd (character) variable label used title rendering. visit_levels (character) variable levels studied visits. visit_var (character) variable names can used visit variable. Must factor dataname. conf_level (numeric) value confidence level within range (0, 1). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_ancova.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: ANCOVA Summary — template_ancova","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_arguments.html","id":null,"dir":"Reference","previous_headings":"","what":"Standard Template Arguments — template_arguments","title":"Standard Template Arguments — template_arguments","text":"documentation function lists arguments teal module templates used repeatedly express analysis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_arguments.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Standard Template Arguments — template_arguments","text":"add_total (logical) whether include column total number patients. anl_name (character) analysis data used teal module. arm_var (character) variable names can used arm_var. atirel (character) name time relation medication variable. aval Please use aval_var argument instead. avalu Please use avalu_var argument instead. avalu_var (character) name analysis value unit variable. aval_var (character) name analysis value variable. baseline_var (character) name variable baseline values analysis variable. base_var Please use baseline_var argument instead. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). by_vars (character) variable names used split summary rows. cmdecod (character) name standardized medication name variable. cmindc (character) name indication variable. cmstdy (character) name study relative day start medication variable. cnsr_var (character) name censoring variable. combine_comp_arms (logical) triggers combination comparison arms. compare_arm (logical) triggers comparison study arms. comp_arm (character) level comparison arm case arm comparison. conf_level (numeric) value confidence level within range (0, 1). control (list) list settings analysis. cov_var (character) names covariates variables. dataname (character) analysis data used teal module. denominator (character) chooses percentages calculated. option N, reference population column total used denominator. option n, number non-missing records row column intersection used denominator. omit chosen, percentage omitted. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. event_type (character) type event summarized (e.g. adverse event, treatment). Default \"event\". font_size (numeric) font size value. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). hlt (character) name variable high level term events. id_var (character) variable name subject id. include_interact (logical) whether interaction term included model. label_hlt (string) label hlt variable dataname. label extracted module. label_llt (string) label llt variable dataname. label extracted module. llt (character) name variable low level term events. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). na.rm (logical) whether NA values removed prior analysis. numeric_stats (character) names statistics display numeric summary variables. Available statistics n, mean_sd, mean_ci, median, median_ci, quantiles, range, geom_mean. paramcd (character) name parameter code variable. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_id (character) patient ID. prune_diff (number) threshold use trimming table using criteria difference rates two columns. prune_freq (number) threshold use trimming table using event incidence rate column. ref_arm (character) level reference arm case arm comparison. sort_criteria (character) sort final table. Default option freq_desc sorts column sort_freq_col decreasing number patients event. Alternative option alpha sorts events alphabetically. strata_var (character) names variables stratified analysis. subgroup_var (character) variable names can used subgroups. sum_vars (character) names variables summarized. time_points (character) time points can used tern::surv_timepoint(). time_unit_var (character) name variable representing time units. title (character) title output. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). treatment_flag (character) name value indicating treatment records treatment_flag_var. treatment_flag_var (character) name treatment flag variable. useNA (character) whether missing data (NA) displayed level. var_labels (named character) optional variable labels relabeling analysis variables. visit_var (character) variable names can used visit variable. Must factor dataname. worst_flag_indicator (character) value indicating worst grade. worst_flag_var (character) name worst flag variable.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_arguments.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Standard Template Arguments — template_arguments","text":"list expressions generate table plot object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_arguments.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Standard Template Arguments — template_arguments","text":"Although function just returns NULL two uses, teal module users provides documentation arguments commonly consistently used framework. developer adds single reference point import roxygen argument description : @inheritParams template_arguments","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_basic_info.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Basic Info — template_basic_info","title":"Template: Patient Profile Basic Info — template_basic_info","text":"Creates valid expression generate patient profile basic info report using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_basic_info.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Basic Info — template_basic_info","text":"","code":"template_basic_info(dataname = \"ANL\", vars, patient_id = NULL)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_basic_info.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Basic Info — template_basic_info","text":"dataname (character) analysis data used teal module. vars (character) names variables shown table. patient_id (character) patient ID.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_basic_info.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Basic Info — template_basic_info","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_binary_outcome.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Binary Outcome — template_binary_outcome","title":"Template: Binary Outcome — template_binary_outcome","text":"Creates valid expression generate binary outcome analysis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_binary_outcome.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Binary Outcome — template_binary_outcome","text":"","code":"template_binary_outcome( dataname, parentname, arm_var, paramcd, ref_arm = NULL, comp_arm = NULL, compare_arm = FALSE, combine_comp_arms = FALSE, aval_var = \"AVALC\", show_rsp_cat = TRUE, responder_val = c(\"Complete Response (CR)\", \"Partial Response (PR)\"), responder_val_levels = responder_val, control = list(global = list(method = \"waldcc\", conf_level = 0.95), unstrat = list(method_ci = \"waldcc\", method_test = \"schouten\", odds = TRUE), strat = list(method_ci = \"cmh\", method_test = \"cmh\", strat = NULL)), add_total = FALSE, total_label = default_total_label(), na_level = default_na_str(), basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_binary_outcome.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Binary Outcome — template_binary_outcome","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. paramcd (character) response parameter value use table title. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. compare_arm (logical) triggers comparison study arms. combine_comp_arms (logical) triggers combination comparison arms. aval_var (character) name analysis value variable. show_rsp_cat (logical) display multinomial response estimations. responder_val (character) short label observations translate AVALC responder/non-responder. responder_val_levels (character) levels responses shown multinomial response estimations. control (list) list settings analysis. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_binary_outcome.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Binary Outcome — template_binary_outcome","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_coxreg_m.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Multi-Variable Cox Regression — template_coxreg_m","title":"Template: Multi-Variable Cox Regression — template_coxreg_m","text":"Creates valid expression generate multi-variable Cox regression analysis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_coxreg_m.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Multi-Variable Cox Regression — template_coxreg_m","text":"","code":"template_coxreg_m( dataname, cov_var, arm_var, cnsr_var, aval_var, ref_arm, comp_arm, paramcd, at = list(), strata_var = NULL, combine_comp_arms = FALSE, control = control_coxreg(), na_level = default_na_str(), basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_coxreg_m.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Multi-Variable Cox Regression — template_coxreg_m","text":"dataname (character) analysis data used teal module. cov_var (character) names covariates variables. arm_var (character) variable names can used arm_var. cnsr_var (character) name censoring variable. aval_var (character) name analysis value variable. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. paramcd (character) name parameter code variable. (list numeric) candidate covariate numeric type variable, use specify value covariate effect estimated. strata_var (character) names variables stratified analysis. combine_comp_arms (logical) triggers combination comparison arms. control (list) list settings analysis (see tern::control_coxreg()). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_coxreg_m.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Multi-Variable Cox Regression — template_coxreg_m","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_coxreg_u.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Univariable Cox Regression — template_coxreg_u","title":"Template: Univariable Cox Regression — template_coxreg_u","text":"Creates valid expression generate univariable Cox regression analysis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_coxreg_u.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Univariable Cox Regression — template_coxreg_u","text":"","code":"template_coxreg_u( dataname, cov_var, arm_var, cnsr_var, aval_var, ref_arm, comp_arm, paramcd, at = list(), strata_var = NULL, combine_comp_arms = FALSE, control = control_coxreg(), na_level = default_na_str(), append = FALSE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_coxreg_u.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Univariable Cox Regression — template_coxreg_u","text":"dataname (character) analysis data used teal module. cov_var (character) names covariates variables. arm_var (character) variable names can used arm_var. cnsr_var (character) name censoring variable. aval_var (character) name analysis value variable. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. paramcd (character) name parameter code variable. (list numeric) candidate covariate numeric type variable, use specify value covariate effect estimated. strata_var (character) names variables stratified analysis. combine_comp_arms (logical) triggers combination comparison arms. control (list) list settings analysis (see tern::control_coxreg()). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). append (logical) whether result appended previous one. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_coxreg_u.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Univariable Cox Regression — template_coxreg_u","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Events by Term — template_events","title":"Template: Events by Term — template_events","text":"Creates valid expression generate table events term.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Events by Term — template_events","text":"","code":"template_events( dataname, parentname, arm_var, hlt, llt, label_hlt = NULL, label_llt = NULL, add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), event_type = \"event\", sort_criteria = c(\"freq_desc\", \"alpha\"), sort_freq_col = total_label, prune_freq = 0, prune_diff = 0, drop_arm_levels = TRUE, incl_overall_sum = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Events by Term — template_events","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. hlt (character) name variable high level term events. llt (character) name variable low level term events. label_hlt (string) label hlt variable dataname. label extracted module. label_llt (string) label llt variable dataname. label extracted module. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). event_type (character) type event summarized (e.g. adverse event, treatment). Default \"event\". sort_criteria (character) sort final table. Default option freq_desc sorts column sort_freq_col decreasing number patients event. Alternative option alpha sorts events alphabetically. sort_freq_col (character) column sort frequency sort_criteria set freq_desc. prune_freq (number) threshold use trimming table using event incidence rate column. prune_diff (number) threshold use trimming table using criteria difference rates two columns. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. incl_overall_sum (flag) whether two rows summarize overall number adverse events included top table. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Events by Term — template_events","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_by_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Events by Grade — template_events_by_grade","title":"Template: Events by Grade — template_events_by_grade","text":"Creates valid expression generate table summarize events grade.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_by_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Events by Grade — template_events_by_grade","text":"","code":"template_events_by_grade( dataname, parentname, arm_var, id = \"\", hlt, llt, label_hlt = NULL, label_llt = NULL, grade, label_grade = NULL, prune_freq = 0, prune_diff = 0, add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), drop_arm_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_by_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Events by Grade — template_events_by_grade","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. id (character) unique identifier patients datasets, default \"USUBJID\". hlt (character) name variable high level term events. llt (character) name variable low level term events. label_hlt (string) label hlt variable dataname. label extracted module. label_llt (string) label llt variable dataname. label extracted module. grade (character) name severity level variable. label_grade (string) label grade variable dataname. label extracted module. prune_freq (number) threshold use trimming table using event incidence rate column. prune_diff (number) threshold use trimming table using criteria difference rates two columns. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_by_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Events by Grade — template_events_by_grade","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_col_by_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Adverse Events Grouped by Grade with Threshold — template_events_col_by_grade","title":"Template: Adverse Events Grouped by Grade with Threshold — template_events_col_by_grade","text":"Creates valid expression generate table summarize adverse events grouped grade.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_col_by_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Adverse Events Grouped by Grade with Threshold — template_events_col_by_grade","text":"","code":"template_events_col_by_grade( dataname, parentname, arm_var, grading_groups = list(`Any Grade (%)` = c(\"1\", \"2\", \"3\", \"4\", \"5\"), `Grade 1-2 (%)` = c(\"1\", \"2\"), `Grade 3-4 (%)` = c(\"3\", \"4\"), `Grade 5 (%)` = \"5\"), add_total = TRUE, total_label = default_total_label(), id = \"USUBJID\", hlt, llt, label_hlt = NULL, label_llt = NULL, grade = \"AETOXGR\", label_grade = NULL, prune_freq = 0.1, prune_diff = 0, na_level = default_na_str(), drop_arm_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_col_by_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Adverse Events Grouped by Grade with Threshold — template_events_col_by_grade","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. grading_groups (list) named list grading groups. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). id (character) name variable uniquely identify patients datasets. hlt (character) name variable high level term events. llt (character) name variable low level term events. label_hlt (string) label hlt variable dataname. label extracted module. label_llt (string) label llt variable dataname. label extracted module. grade (character) name grade variable base grading_groups . label_grade (character) label grade variable dataname. prune_freq (number) threshold use trimming table using event incidence rate column. prune_diff (number) threshold use trimming table using criteria difference rates two columns. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_col_by_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Adverse Events Grouped by Grade with Threshold — template_events_col_by_grade","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_patyear.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Event Rates Adjusted for Patient-Years — template_events_patyear","title":"Template: Event Rates Adjusted for Patient-Years — template_events_patyear","text":"Creates valid expression generate table event rates adjusted patient-years.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_patyear.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Event Rates Adjusted for Patient-Years — template_events_patyear","text":"","code":"template_events_patyear( dataname, parentname, arm_var, events_var, label_paramcd, aval_var = \"AVAL\", add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), control = control_incidence_rate(), drop_arm_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_patyear.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Event Rates Adjusted for Patient-Years — template_events_patyear","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. events_var (character) name variable number observed events. label_paramcd (character)paramcd variable text use table title. aval_var (character) name analysis value variable. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). control (list) list settings analysis. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_patyear.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Event Rates Adjusted for Patient-Years — template_events_patyear","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_summary.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Adverse Events Summary — template_events_summary","title":"Template: Adverse Events Summary — template_events_summary","text":"Creates valid expression generate adverse events summary table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_summary.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Adverse Events Summary — template_events_summary","text":"","code":"template_events_summary( anl_name, parentname, arm_var, dthfl_var = \"DTHFL\", dcsreas_var = \"DCSREAS\", flag_var_anl = NULL, flag_var_aesi = NULL, aeseq_var = \"AESEQ\", llt = \"AEDECOD\", add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), count_dth = TRUE, count_wd = TRUE, count_subj = TRUE, count_pt = TRUE, count_events = TRUE )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_summary.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Adverse Events Summary — template_events_summary","text":"anl_name (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. dthfl_var (character) name variable subject death flag parentname. Records \"Y\" summarized table row \"Total number deaths\". dcsreas_var (character) name variable study discontinuation reason parentname. Records \"ADVERSE EVENTS\" summarized table row \"Total number patients withdrawn study due AE\". flag_var_anl (character) name flag variable dataset used count adverse event sub-groups (e.g. Serious events, Related events, etc.). Variable labels used table row names exist. flag_var_aesi (character) name flag variable dataset used count adverse event special interest groups. flag variables must type logical. Variable labels used table row names exist. aeseq_var (character) name variable adverse events sequence number dataset. Used counting total number events. llt (character) name variable low level term events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). count_dth (logical) whether show count total deaths (based dthfl_var). Defaults TRUE. count_wd (logical) whether show count patients withdrawn study due adverse event (based dcsreas_var). Defaults TRUE. count_subj (logical) whether show count unique subjects (based USUBJID). applies event flag variables provided. count_pt (logical) whether show count unique preferred terms (based llt). applies event flag variables provided. count_events (logical) whether show count events (based aeseq_var). applies event flag variables provided.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_events_summary.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Adverse Events Summary — template_events_summary","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_exposure.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Exposure Table for Risk management plan — template_exposure","title":"Template: Exposure Table for Risk management plan — template_exposure","text":"Creates valid expression generate exposure table risk management plan.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_exposure.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Exposure Table for Risk management plan — template_exposure","text":"","code":"template_exposure( parentname, dataname, id_var, paramcd, paramcd_label = NULL, row_by_var, col_by_var = NULL, add_total = FALSE, total_label = \"Total\", add_total_row = TRUE, total_row_label = \"Total number of patients and patient time*\", drop_levels = TRUE, na_level = default_na_str(), aval_var, avalu_var, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_exposure.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Exposure Table for Risk management plan — template_exposure","text":"parentname (character) parent analysis data used teal module, usually refers ADSL. dataname (character) analysis data used teal module. id_var (character) variable name subject id. paramcd (character) name parameter code variable. paramcd_label (character) column dataname dataset value used label argument paramcd. row_by_var (character) variable name used split values rows. col_by_var (character) variable name used split values columns. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). add_total_row (flag) whether \"total\" level added others includes levels constitute split. custom label can set level via total_row_label argument. total_row_label (character) string display total row label row enabled (see add_total_row). drop_levels (flag) whether empty rows removed table. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). aval_var (character) name analysis value variable. avalu_var (character) name analysis value unit variable. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_exposure.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Exposure Table for Risk management plan — template_exposure","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_fit_mmrm.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm","title":"Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm","text":"Creates valid expression generate analysis tables plots Mixed Model Repeated Measurements.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_fit_mmrm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm","text":"","code":"template_fit_mmrm( parentname, dataname, aval_var, arm_var, ref_arm, comp_arm = NULL, combine_comp_arms = FALSE, id_var, visit_var, cov_var, conf_level = 0.95, method = \"Satterthwaite\", cor_struct = \"unstructured\", weights_emmeans = \"proportional\", parallel = FALSE ) template_mmrm_tables( parentname, dataname, fit_name, arm_var, ref_arm, visit_var, paramcd, show_relative = c(\"increase\", \"reduction\", \"none\"), table_type = \"t_mmrm_cov\", total_label = default_total_label(), basic_table_args = teal.widgets::basic_table_args() ) template_mmrm_plots( fit_name, lsmeans_plot = list(select = c(\"estimates\", \"contrasts\"), width = 0.6, show_pval = FALSE), diagnostic_plot = list(type = \"fit-residual\", z_threshold = NULL), ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_fit_mmrm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm","text":"parentname (character) parent analysis data used teal module, usually refers ADSL. dataname (character) analysis data used teal module. aval_var (character) name analysis value variable. arm_var (character) variable names can used arm_var. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. combine_comp_arms (logical) triggers combination comparison arms. id_var (character) variable name subject id. visit_var (character) variable names can used visit variable. Must factor dataname. cov_var (character) names covariates variables. conf_level (numeric) value confidence level within range (0, 1). method (string) string specifying adjustment method. cor_struct (string) string specifying correlation structure, defaults \"unstructured\". See tern.mmrm::build_formula() options. weights_emmeans argument emmeans::emmeans(), \"proportional\" default. parallel (flag) flag controls whether optimizer search can use available free cores machine (default). fit_name (string) name fitted MMRM object. paramcd (character) name parameter code variable. show_relative (string) \"reduction\" (control - treatment, default) \"increase\" (treatment - control) shown relative change baseline. table_type (string) type table output. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). lsmeans_plot (named list) list controls LS means plot. See tern.mmrm::g_mmrm_lsmeans(). diagnostic_plot (named list) list controls diagnostic_plot. See tern.mmrm::g_mmrm_diagnostic(). ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_fit_mmrm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm","text":"list expressions generate table plot object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_fit_mmrm.html","id":"functions","dir":"Reference","previous_headings":"","what":"Functions","title":"Template: Mixed Model Repeated Measurements (MMRM) Analysis — template_fit_mmrm","text":"template_mmrm_tables(): Creates valid expressions generate MMRM LS means, covariance matrix, fixed effects, diagnostic tables. template_mmrm_plots(): Creates valid expressions generate MMRM LS means diagnostic plots.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_forest_rsp.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Response Forest Plot — template_forest_rsp","title":"Template: Response Forest Plot — template_forest_rsp","text":"Creates valid expression generate response forest plot.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_forest_rsp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Response Forest Plot — template_forest_rsp","text":"","code":"template_forest_rsp( dataname = \"ANL\", parentname = \"ADSL\", arm_var, ref_arm = NULL, comp_arm = NULL, obj_var_name = \"\", aval_var = \"AVALC\", responders = c(\"CR\", \"PR\"), subgroup_var, strata_var = NULL, stats = c(\"n_tot\", \"n\", \"n_rsp\", \"prop\", \"or\", \"ci\"), riskdiff = NULL, conf_level = 0.95, col_symbol_size = NULL, rel_width_forest = 0.25, font_size = 15, ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_forest_rsp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Response Forest Plot — template_forest_rsp","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. obj_var_name (character) additional text append table title. aval_var (character) name analysis value variable. responders (character) values aval_var considered responders. subgroup_var (character) variable names can used subgroups. strata_var (character) names variables stratified analysis. stats (character) names statistics reported among: n: Total number observations per group. n_rsp: Number responders per group. prop: Proportion responders. n_tot: Total number observations. : Odds ratio. ci : Confidence interval odds ratio. pval: p-value effect. Note, statistics n_tot, , ci required. riskdiff (list) risk (proportion) difference column added, list settings apply within column. See tern::control_riskdiff() details. NULL, risk difference column added. conf_level (numeric) value confidence level within range (0, 1). col_symbol_size (integer NULL) column index used determine relative size estimator plot symbol. Typically, symbol size proportional sample size used calculate estimator. NULL, symbol size used subgroups. rel_width_forest (proportion) proportion total width allocate forest plot. Relative width table 1 - rel_width_forest. as_list = TRUE, parameter ignored. font_size (numeric(1)) font size. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. module, argument accept ggplot2_args object labs list following child elements: title, caption. elements taken account. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_forest_rsp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Response Forest Plot — template_forest_rsp","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_forest_tte.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Survival Forest Plot — template_forest_tte","title":"Template: Survival Forest Plot — template_forest_tte","text":"Creates valid expression generate survival forest plot.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_forest_tte.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Survival Forest Plot — template_forest_tte","text":"","code":"template_forest_tte( dataname = \"ANL\", parentname = \"ANL_ADSL\", arm_var, ref_arm = NULL, comp_arm = NULL, obj_var_name = \"\", aval_var = \"AVAL\", cnsr_var = \"CNSR\", subgroup_var, strata_var = NULL, stats = c(\"n_tot_events\", \"n_events\", \"median\", \"hr\", \"ci\"), riskdiff = NULL, conf_level = 0.95, col_symbol_size = NULL, time_unit_var = \"AVALU\", rel_width_forest = 0.25, font_size = 15, ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_forest_tte.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Survival Forest Plot — template_forest_tte","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. obj_var_name (character) additional text append table title. aval_var (character) name analysis value variable. cnsr_var (character) name censoring variable. subgroup_var (character) variable names can used subgroups. strata_var (character) names variables stratified analysis. stats (character) names statistics reported among: n_tot_events: Total number events per group. n_events: Number events per group. n_tot: Total number observations per group. n: Number observations per group. median: Median survival time. hr: Hazard ratio. ci: Confidence interval hazard ratio. pval: p-value effect. Note, one statistics n_tot n_tot_events, well hr ci required. riskdiff (list) risk (proportion) difference column added, list settings apply within column. See tern::control_riskdiff() details. NULL, risk difference column added. conf_level (numeric) value confidence level within range (0, 1). col_symbol_size (integer NULL) column index used determine relative size estimator plot symbol. Typically, symbol size proportional sample size used calculate estimator. NULL, symbol size used subgroups. time_unit_var (character) name variable representing time units. rel_width_forest (proportion) proportion total width allocate forest plot. Relative width table 1 - rel_width_forest. as_list = TRUE, parameter ignored. font_size (numeric) font size value. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_forest_tte.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Survival Forest Plot — template_forest_tte","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_ci.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Confidence Interval Plot — template_g_ci","title":"Template: Confidence Interval Plot — template_g_ci","text":"Creates valid expression generate ggplot2::ggplot() confidence interval plot.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_ci.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Confidence Interval Plot — template_g_ci","text":"","code":"template_g_ci( dataname, x_var, y_var, grp_var = NULL, stat = c(\"mean\", \"median\"), conf_level = 0.95, unit_var = \"AVALU\", ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_ci.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Confidence Interval Plot — template_g_ci","text":"dataname (character) analysis data used teal module. x_var (character) name treatment variable put x-axis. y_var (character) name response variable put y-axis. grp_var (character) name group variable used determine plot colors, point shapes, line types. stat (character) statistic plot. Options \"mean\" \"median\". conf_level (numeric) value confidence level within range (0, 1). unit_var (character) name unit variable. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_ci.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Confidence Interval Plot — template_g_ci","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_ipp.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Individual Patient Plots — template_g_ipp","title":"Template: Individual Patient Plots — template_g_ipp","text":"Creates valid expression generate ggplot2::ggplot() plots individual patients.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_ipp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Individual Patient Plots — template_g_ipp","text":"","code":"template_g_ipp( dataname = \"ANL\", paramcd, arm_var, arm_levels, avalu_first, paramcd_first, aval_var = \"AVAL\", avalu_var = \"AVALU\", id_var = \"USUBJID\", visit_var = \"AVISIT\", base_var = lifecycle::deprecated(), baseline_var = \"BASE\", add_baseline_hline = FALSE, separate_by_obs = FALSE, ggplot2_args = teal.widgets::ggplot2_args(), suppress_legend = FALSE, add_avalu = TRUE )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_ipp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Individual Patient Plots — template_g_ipp","text":"dataname (character) analysis data used teal module. paramcd (character) name parameter code variable. arm_var (character) variable names can used arm_var. arm_levels (character) vector levels arm_var. avalu_first (character)avalu_var text append plot title y-axis label add_avalu TRUE. paramcd_first (character)paramcd text append plot title y-axis label. aval_var (character) name analysis value variable. avalu_var (character) name analysis value unit variable. id_var (character) variable name subject id. visit_var (character) name variable visit timepoints. base_var Please use baseline_var argument instead. baseline_var (character) name variable baseline values analysis variable. add_baseline_hline (logical) whether horizontal line added plot baseline y-value. separate_by_obs (logical) whether create multi-panel plots. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. module, argument accept ggplot2_args object labs list following child elements: title, subtitle, x, y. elements taken account. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). suppress_legend (logical) whether suppress plot legend. add_avalu (logical) whether avalu_first text appended plot title y-axis label.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_ipp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Individual Patient Plots — template_g_ipp","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_km.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Kaplan-Meier Plot — template_g_km","title":"Template: Kaplan-Meier Plot — template_g_km","text":"Creates valid expression generate Kaplan-Meier plot.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_km.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Kaplan-Meier Plot — template_g_km","text":"","code":"template_g_km( dataname = \"ANL\", arm_var = \"ARM\", ref_arm = NULL, comp_arm = NULL, compare_arm = FALSE, combine_comp_arms = FALSE, aval_var = \"AVAL\", cnsr_var = \"CNSR\", xticks = NULL, strata_var = NULL, time_points = NULL, facet_var = \"SEX\", font_size = 11, conf_level = 0.95, ties = \"efron\", xlab = \"Survival time\", time_unit_var = \"AVALU\", yval = \"Survival\", ylim = NULL, pval_method = \"log-rank\", annot_surv_med = TRUE, annot_coxph = TRUE, control_annot_surv_med = control_surv_med_annot(), control_annot_coxph = control_coxph_annot(x = 0.27, y = 0.35, w = 0.3), legend_pos = NULL, position_coxph = lifecycle::deprecated(), width_annots = lifecycle::deprecated(), rel_height_plot = 0.8, ci_ribbon = FALSE, title = \"KM Plot\" )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_km.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Kaplan-Meier Plot — template_g_km","text":"dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. compare_arm (logical) triggers comparison study arms. combine_comp_arms (logical) triggers combination comparison arms. aval_var (character) name analysis value variable. cnsr_var (character) name censoring variable. xticks (numeric NULL) numeric vector tick positions single number spacing ticks x-axis. NULL (default), labeling::extended() used determine optimal tick positions x-axis. strata_var (character) names variables stratified analysis. time_points (character) time points can used tern::surv_timepoint(). facet_var (character) name variable use facet plot. font_size (numeric) font size value. conf_level (numeric) value confidence level within range (0, 1). ties (string) among exact (equivalent DISCRETE SAS), efron breslow, see survival::coxph(). Note: equivalent SAS EXACT method R. xlab (string) x-axis label. time_unit_var (character) name variable representing time units. yval (string) type plot, plotted y-axis. Options Survival (default) Failure probability. ylim (numeric(2)) vector containing lower upper limits y-axis, respectively. NULL (default), default scale range used. pval_method (string) method used estimation p.values; wald (default) likelihood. annot_surv_med (flag) compute add annotation table Kaplan-Meier curve estimating median survival time per group. annot_coxph (flag) whether add annotation table survival::coxph() model. control_annot_surv_med (list) parameters control position size annotation table added plot annot_surv_med = TRUE, specified using control_surv_med_annot() function. Parameter options : x, y, w, h, fill. See control_surv_med_annot() details. control_annot_coxph (list) parameters control position size annotation table added plot annot_coxph = TRUE, specified using control_coxph_annot() function. Parameter options : x, y, w, h, fill, ref_lbls. See control_coxph_annot() details. legend_pos (numeric(2) NULL) vector containing x- y-coordinates, respectively, legend position relative KM plot area. NULL (default), legend positioned bottom right corner plot, middle right plot needed prevent overlapping. position_coxph Please use x y elements control_annot_coxph instead. width_annots Please use w element control_annot_surv_med (surv_med) control_annot_coxph (coxph).\" rel_height_plot (proportion) proportion total figure height allocate Kaplan-Meier plot. Relative height patients risk table 1 - rel_height_plot. annot_at_risk = FALSE as_list = TRUE, parameter ignored. ci_ribbon (flag) whether confidence interval drawn around Kaplan-Meier curve. title (character) title output.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_km.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Kaplan-Meier Plot — template_g_km","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_lineplot.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Line Plot — template_g_lineplot","title":"Template: Line Plot — template_g_lineplot","text":"Creates valid expression generate ggplot2::ggplot() line plot.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_lineplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Line Plot — template_g_lineplot","text":"","code":"template_g_lineplot( dataname = \"ANL\", strata = lifecycle::deprecated(), group_var = \"ARM\", x = \"AVISIT\", y = \"AVAL\", y_unit = \"AVALU\", paramcd = \"PARAMCD\", param = \"ALT\", mid = \"mean\", interval = \"mean_ci\", whiskers = c(\"mean_ci_lwr\", \"mean_ci_upr\"), table = c(\"n\", \"mean_sd\", \"median\", \"range\"), mid_type = \"pl\", conf_level = 0.95, incl_screen = TRUE, mid_point_size = 2, table_font_size = 4, title = \"Line Plot\", y_lab = \"\", ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_lineplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Line Plot — template_g_lineplot","text":"dataname (character) analysis data used teal module. strata Please use group_var argument instead. group_var (string NA) group variable name. x (string) x-variable name. y (string) y-variable name. y_unit (string NA) y-axis unit variable name. paramcd (string NA) parameter code variable name. param (character) parameter filter data . mid (character NULL) names statistics plotted midpoints. statistics indicated mid variable must present object returned sfun, double numeric type vector length one. interval (character NULL) names statistics plotted intervals. statistics indicated interval variable must present object returned sfun, double numeric type vector length two. Set interval = NULL intervals added plot. whiskers (character) names interval whiskers plotted. Names must match names list element interval returned sfun (e.g. mean_ci_lwr element sfun(x)[[\"mean_ci\"]]). possible specify one whisker , suppress whiskers setting interval = NULL. table (character NULL) names statistics displayed table plot. statistics indicated table variable must present object returned sfun. mid_type (string) controls type mid plot, can point (\"p\"), line (\"l\"), point line (\"pl\"). conf_level (numeric) value confidence level within range (0, 1). incl_screen (logical) whether screening visit included. mid_point_size (numeric(1)) font size mid plot points. table_font_size (numeric(1)) font size text table. title (string) plot title. y_lab (string NULL) y-axis label. NULL label added. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. module, argument accept ggplot2_args object labs list following child elements: title, subtitle, caption, y, lty. elements taken account. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_g_lineplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Line Plot — template_g_lineplot","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_laboratory.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Laboratory Table — template_laboratory","title":"Template: Patient Profile Laboratory Table — template_laboratory","text":"Creates valid expression generate patient profile laboratory table using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_laboratory.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Laboratory Table — template_laboratory","text":"","code":"template_laboratory( dataname = \"ANL\", paramcd = \"PARAMCD\", param = \"PARAM\", anrind = \"ANRIND\", timepoints = \"ADY\", aval = lifecycle::deprecated(), aval_var = \"AVAL\", avalu = lifecycle::deprecated(), avalu_var = \"AVALU\", patient_id = NULL, round_value = 0L )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_laboratory.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Laboratory Table — template_laboratory","text":"dataname (character) analysis data used teal module. paramcd (character) name parameter code variable. param (character) name parameter variable. anrind (character) name analysis reference range indicator variable. timepoints (character) name time variable. aval Please use aval_var argument instead. aval_var (character) name analysis value variable. avalu Please use avalu_var argument instead. avalu_var (character) name analysis value unit variable. patient_id (character) patient ID. round_value (numeric) number decimal places round .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_laboratory.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Laboratory Table — template_laboratory","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_logistic.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Logistic Regression — template_logistic","title":"Template: Logistic Regression — template_logistic","text":"Creates valid expression generate logistic regression table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_logistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Logistic Regression — template_logistic","text":"","code":"template_logistic( dataname, arm_var, aval_var, paramcd = lifecycle::deprecated(), label_paramcd, cov_var, interaction_var, ref_arm, comp_arm, topleft = \"Logistic Regression\", conf_level = 0.95, combine_comp_arms = FALSE, responder_val = c(\"CR\", \"PR\"), at = NULL, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_logistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Logistic Regression — template_logistic","text":"dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. fit logistic model arm/treatment variable, set NULL. aval_var (character) name analysis value variable. paramcd paramcd argument used function. label_paramcd (character) label response parameter value print table title. cov_var (character) names covariates variables. interaction_var (character) names variables can used interaction variable selection. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. topleft (character) text use top-left annotation table. conf_level (numeric) value confidence level within range (0, 1). combine_comp_arms (logical) triggers combination comparison arms. responder_val (character) values responder variable corresponding successful response. (numeric NULL) optional values interaction variable. Otherwise median used. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_logistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Logistic Regression — template_logistic","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_medical_history.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Medical History — template_medical_history","title":"Template: Patient Profile Medical History — template_medical_history","text":"Creates valid expression generate patient profile medical history report using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_medical_history.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Medical History — template_medical_history","text":"","code":"template_medical_history( dataname = \"ANL\", mhterm = \"MHTERM\", mhbodsys = \"MHBODSYS\", mhdistat = \"MHDISTAT\", patient_id = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_medical_history.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Medical History — template_medical_history","text":"dataname (character) analysis data used teal module. mhterm (character) name reported term medical history variable. mhbodsys (character) name body system organ class variable. mhdistat (character) name status disease variable. patient_id (character) patient ID.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_medical_history.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Medical History — template_medical_history","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_mult_events.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Multiple Events by Term — template_mult_events","title":"Template: Multiple Events by Term — template_mult_events","text":"Creates valid expression generate table multiple events term.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_mult_events.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Multiple Events by Term — template_mult_events","text":"","code":"template_mult_events( dataname, parentname, arm_var, seq_var, hlt, llt, add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), event_type = \"event\", drop_arm_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_mult_events.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Multiple Events by Term — template_mult_events","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. seq_var (character) name analysis sequence number variable. Used counting unique number events. hlt (character) name variable high level term events. llt (character) name variable low level term events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). event_type (character) type event summarized (e.g. adverse event, treatment). Default \"event\". drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_mult_events.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Multiple Events by Term — template_mult_events","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_patient_timeline.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Timeline Plot — template_patient_timeline","title":"Template: Patient Profile Timeline Plot — template_patient_timeline","text":"Creates valid expression generate patient profile timeline ggplot2::ggplot() plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_patient_timeline.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Timeline Plot — template_patient_timeline","text":"","code":"template_patient_timeline( dataname = \"ANL\", aeterm = \"AETERM\", aetime_start = \"ASTDTM\", aetime_end = \"AENDTM\", dstime_start = \"CMASTDTM\", dstime_end = \"CMAENDTM\", cmdecod = \"CMDECOD\", aerelday_start = NULL, aerelday_end = NULL, dsrelday_start = NULL, dsrelday_end = NULL, relative_day = FALSE, patient_id, font_size = 12L, ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_patient_timeline.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Timeline Plot — template_patient_timeline","text":"dataname (character) analysis data used teal module. aeterm (character) name reported term adverse event variable. aetime_start (character) name start date/time adverse event variable. aetime_end (character) name end date/time adverse event variable. dstime_start (character) name date/time first exposure treatment variable. dstime_end (character) name date/time last exposure treatment variable. cmdecod (character) name standardized medication name variable. aerelday_start (character) name adverse event study start day variable. aerelday_end (character) name adverse event study end day variable. dsrelday_start (character) name concomitant medications study start day variable. dsrelday_end (character) name concomitant medications study day start variable. relative_day (logical) whether use relative days (TRUE) absolute dates (FALSE). patient_id (character) patient ID. font_size (numeric) font size value. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_patient_timeline.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Timeline Plot — template_patient_timeline","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_prior_medication.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Prior Medication — template_prior_medication","title":"Template: Patient Profile Prior Medication — template_prior_medication","text":"Creates valid expression generate patient profile prior medication report using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_prior_medication.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Prior Medication — template_prior_medication","text":"","code":"template_prior_medication( dataname = \"ANL\", atirel = \"ATIREL\", cmdecod = \"CMDECOD\", cmindc = \"CMINDC\", cmstdy = \"CMSTDY\" )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_prior_medication.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Prior Medication — template_prior_medication","text":"dataname (character) analysis data used teal module. atirel (character) name time relation medication variable. cmdecod (character) name standardized medication name variable. cmindc (character) name indication variable. cmstdy (character) name study relative day start medication variable.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_prior_medication.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Prior Medication — template_prior_medication","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_shift_by_arm.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Shift by Arm — template_shift_by_arm","title":"Template: Shift by Arm — template_shift_by_arm","text":"Creates valid expression generate summary table analysis indicator levels arm.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_shift_by_arm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Shift by Arm — template_shift_by_arm","text":"","code":"template_shift_by_arm( dataname, parentname, arm_var = \"ARM\", paramcd = \"PARAMCD\", visit_var = \"AVISIT\", treatment_flag_var = \"ONTRTFL\", treatment_flag = \"Y\", aval_var = \"ANRIND\", base_var = lifecycle::deprecated(), baseline_var = \"BNRIND\", na.rm = FALSE, na_level = default_na_str(), add_total = FALSE, total_label = default_total_label(), basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_shift_by_arm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Shift by Arm — template_shift_by_arm","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. paramcd (character) name parameter code variable. visit_var (character) variable names can used visit variable. Must factor dataname. treatment_flag_var (character) name treatment flag variable. treatment_flag (character) name value indicating treatment records treatment_flag_var. aval_var (character) name analysis reference range indicator variable. base_var Please use baseline_var argument instead. baseline_var (character) name baseline reference range indicator variable. na.rm (logical) whether NA values removed prior analysis. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). add_total (logical) whether include row total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_shift_by_arm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Shift by Arm — template_shift_by_arm","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_shift_by_arm_by_worst.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Shift by Arm by Worst Analysis Indicator Level — template_shift_by_arm_by_worst","title":"Template: Shift by Arm by Worst Analysis Indicator Level — template_shift_by_arm_by_worst","text":"Creates valid expression generate summary table worst analysis indicator variable level per subject arm.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_shift_by_arm_by_worst.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Shift by Arm by Worst Analysis Indicator Level — template_shift_by_arm_by_worst","text":"","code":"template_shift_by_arm_by_worst( dataname, parentname, arm_var = \"ARM\", paramcd = \"PARAMCD\", worst_flag_var = \"WORS02FL\", worst_flag = \"Y\", treatment_flag_var = \"ONTRTFL\", treatment_flag = \"Y\", aval_var = \"ANRIND\", base_var = lifecycle::deprecated(), baseline_var = \"BNRIND\", na.rm = FALSE, na_level = default_na_str(), add_total = FALSE, total_label = default_total_label(), basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_shift_by_arm_by_worst.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Shift by Arm by Worst Analysis Indicator Level — template_shift_by_arm_by_worst","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. paramcd (character) name parameter code variable. worst_flag_var (character) name worst flag variable. worst_flag (character) value indicating worst analysis indicator level. treatment_flag_var (character) name treatment flag variable. treatment_flag (character) name value indicating treatment records treatment_flag_var. aval_var (character) name analysis reference range indicator variable. base_var Please use baseline_var argument instead. baseline_var (character) name baseline reference range indicator variable. na.rm (logical) whether NA values removed prior analysis. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). add_total (logical) whether include row total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_shift_by_arm_by_worst.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Shift by Arm by Worst Analysis Indicator Level — template_shift_by_arm_by_worst","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_shift_by_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Grade Summary Table — template_shift_by_grade","title":"Template: Grade Summary Table — template_shift_by_grade","text":"Creates valid expression generate grade summary table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_shift_by_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Grade Summary Table — template_shift_by_grade","text":"","code":"template_shift_by_grade( parentname, dataname, arm_var = \"ARM\", id_var = \"USUBJID\", visit_var = \"AVISIT\", worst_flag_var = c(\"WGRLOVFL\", \"WGRLOFL\", \"WGRHIVFL\", \"WGRHIFL\"), worst_flag_indicator = \"Y\", anl_toxgrade_var = \"ATOXGR\", base_toxgrade_var = \"BTOXGR\", paramcd = \"PARAMCD\", drop_arm_levels = TRUE, add_total = FALSE, total_label = default_total_label(), na_level = default_na_str(), code_missing_baseline = FALSE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_shift_by_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Grade Summary Table — template_shift_by_grade","text":"parentname (character) parent analysis data used teal module, usually refers ADSL. dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. id_var (character) variable name subject id. visit_var (character) variable names can used visit variable. Must factor dataname. worst_flag_var (character) name worst flag variable. worst_flag_indicator (character) value indicating worst grade. anl_toxgrade_var (character) name variable indicating analysis toxicity grade. base_toxgrade_var (character) name variable indicating baseline toxicity grade. paramcd (character) name parameter code variable. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). code_missing_baseline (logical) whether missing baseline grades counted grade 0. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_shift_by_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Grade Summary Table — template_shift_by_grade","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_smq.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Adverse Events Table by Standardized MedDRA Query — template_smq","title":"Template: Adverse Events Table by Standardized MedDRA Query — template_smq","text":"Creates valid expression generate adverse events table Standardized MedDRA Query.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_smq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Adverse Events Table by Standardized MedDRA Query — template_smq","text":"","code":"template_smq( dataname, parentname, arm_var, llt = \"AEDECOD\", add_total = TRUE, total_label = default_total_label(), sort_criteria = c(\"freq_desc\", \"alpha\"), drop_arm_levels = TRUE, na_level = default_na_str(), smq_varlabel = \"Standardized MedDRA Query\", baskets = c(\"SMQ01NAM\", \"SMQ02NAM\", \"CQ01NAM\"), id_var = \"USUBJID\", basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_smq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Adverse Events Table by Standardized MedDRA Query — template_smq","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. llt (character) name variable low level term events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). sort_criteria (character) sort final table. Default option freq_desc sorts column sort_freq_col decreasing number patients event. Alternative option alpha sorts events alphabetically. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). smq_varlabel (character) label use new column SMQ created tern::h_stack_by_baskets(). baskets (character) names selected standardized/customized queries variables. id_var (character) variable name subject id. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_smq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Adverse Events Table by Standardized MedDRA Query — template_smq","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_summary.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Summary of Variables — template_summary","title":"Template: Summary of Variables — template_summary","text":"Creates valid expression generate table summarize variables.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_summary.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Summary of Variables — template_summary","text":"","code":"template_summary( dataname, parentname, arm_var, sum_vars, show_labels = lifecycle::deprecated(), add_total = TRUE, total_label = default_total_label(), var_labels = character(), arm_var_labels = NULL, na.rm = FALSE, na_level = default_na_str(), numeric_stats = c(\"n\", \"mean_sd\", \"mean_ci\", \"median\", \"median_ci\", \"quantiles\", \"range\", \"geom_mean\"), denominator = c(\"N\", \"n\", \"omit\"), drop_arm_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_summary.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Summary of Variables — template_summary","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. sum_vars (character) names variables summarized. show_labels add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). var_labels (named character) optional variable labels relabeling analysis variables. arm_var_labels (character NULL) vector column variable labels display, length arm_var. NULL, labels displayed. na.rm (logical) whether NA values removed prior analysis. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). numeric_stats (character) names statistics display numeric summary variables. Available statistics n, mean_sd, mean_ci, median, median_ci, quantiles, range, geom_mean. denominator (character) chooses percentages calculated. option N, reference population column total used denominator. option n, number non-missing records row column intersection used denominator. omit chosen, percentage omitted. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_summary.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Summary of Variables — template_summary","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_summary_by.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Summarize Variables by Row Groups Module — template_summary_by","title":"Template: Summarize Variables by Row Groups Module — template_summary_by","text":"Creates valid expression generate table summarize variables row groups.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_summary_by.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Summarize Variables by Row Groups Module — template_summary_by","text":"","code":"template_summary_by( parentname, dataname, arm_var, id_var, sum_vars, by_vars, var_labels = character(), add_total = TRUE, total_label = default_total_label(), parallel_vars = FALSE, row_groups = FALSE, na.rm = FALSE, na_level = default_na_str(), numeric_stats = c(\"n\", \"mean_sd\", \"mean_ci\", \"median\", \"median_ci\", \"quantiles\", \"range\"), denominator = c(\"N\", \"n\", \"omit\"), drop_arm_levels = TRUE, drop_zero_levels = TRUE, basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_summary_by.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Summarize Variables by Row Groups Module — template_summary_by","text":"parentname (character) parent analysis data used teal module, usually refers ADSL. dataname (character) analysis data used teal module. arm_var (character) variable names can used arm_var. id_var (character) variable name subject id. sum_vars (character) names variables summarized. by_vars (character) variable names used split summary rows. var_labels (named character) optional variable labels relabeling analysis variables. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). parallel_vars (logical) whether summarized variables arranged columns. Can set TRUE chosen analysis variables numeric. row_groups (logical) whether summarized variables arranged row groups. na.rm (logical) whether NA values removed prior analysis. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). numeric_stats (character) names statistics display numeric summary variables. Available statistics n, mean_sd, mean_ci, median, median_ci, quantiles, range, geom_mean. denominator (character) chooses percentages calculated. option N, reference population column total used denominator. option n, number non-missing records row column intersection used denominator. omit chosen, percentage omitted. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. drop_zero_levels (logical) whether rows zero counts columns removed table. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_summary_by.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Summarize Variables by Row Groups Module — template_summary_by","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_therapy.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Therapy Table and Plot — template_therapy","title":"Template: Patient Profile Therapy Table and Plot — template_therapy","text":"Creates valid expression generate patient profile therapy table ggplot2::ggplot() plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_therapy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Therapy Table and Plot — template_therapy","text":"","code":"template_therapy( dataname = \"ANL\", atirel = \"ATIREL\", cmdecod = \"CMDECOD\", cmindc = \"CMINDC\", cmdose = \"CMDOSE\", cmtrt = \"CMTRT\", cmdosu = \"CMDOSU\", cmroute = \"CMROUTE\", cmdosfrq = \"CMDOSFRQ\", cmstdy = \"CMSTDY\", cmendy = \"CMENDY\", patient_id, font_size = 12L, ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_therapy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Therapy Table and Plot — template_therapy","text":"dataname (character) analysis data used teal module. atirel (character) name time relation medication variable. cmdecod (character) name standardized medication name variable. cmindc (character) name indication variable. cmdose (character) name dose per administration variable. cmtrt (character) name reported name drug, med, therapy variable. cmdosu (character) name dose units variable. cmroute (character) name route administration variable. cmdosfrq (character) name dosing frequency per interval variable. cmstdy (character) name study relative day start medication variable. cmendy (character) name study day end medication variable. patient_id (character) patient ID. font_size (numeric) font size value. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_therapy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Therapy Table and Plot — template_therapy","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_tte.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Time-To-Event — template_tte","title":"Template: Time-To-Event — template_tte","text":"Creates valid expression generate time--event analysis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_tte.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Time-To-Event — template_tte","text":"","code":"template_tte( dataname = \"ANL\", parentname = \"ADSL\", arm_var = \"ARM\", paramcd, ref_arm = NULL, comp_arm = NULL, compare_arm = FALSE, combine_comp_arms = FALSE, aval_var = \"AVAL\", cnsr_var = \"CNSR\", strata_var = NULL, time_points = NULL, time_unit_var = \"AVALU\", event_desc_var = \"EVNTDESC\", control = control_tte(), add_total = FALSE, total_label = default_total_label(), na_level = default_na_str(), basic_table_args = teal.widgets::basic_table_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_tte.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Time-To-Event — template_tte","text":"dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (character) variable names can used arm_var. paramcd (character) endpoint parameter value use table title. ref_arm (character) level reference arm case arm comparison. comp_arm (character) level comparison arm case arm comparison. compare_arm (logical) triggers comparison study arms. combine_comp_arms (logical) triggers combination comparison arms. aval_var (character) name analysis value variable. cnsr_var (character) name censoring variable. strata_var (character) names variables stratified analysis. time_points (character) time points can used tern::surv_timepoint(). time_unit_var (character) name variable representing time units. event_desc_var (character) name variable events description. control (list) list settings analysis. See control_tte() details. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_tte.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Time-To-Event — template_tte","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_vitals.html","id":null,"dir":"Reference","previous_headings":"","what":"Template: Patient Profile Vitals Plot — template_vitals","title":"Template: Patient Profile Vitals Plot — template_vitals","text":"Creates valid expression generate patient profile vitals ggplot2::ggplot() plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_vitals.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Template: Patient Profile Vitals Plot — template_vitals","text":"","code":"template_vitals( dataname = \"ANL\", paramcd = \"PARAMCD\", paramcd_levels = c(\"SYSBP\", \"DIABP\", \"PUL\", \"RESP\", \"OXYSAT\", \"WGHT\", \"TEMP\"), xaxis = \"ADY\", aval = lifecycle::deprecated(), aval_var = \"AVAL\", patient_id, font_size = 12L, ggplot2_args = teal.widgets::ggplot2_args() )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_vitals.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Template: Patient Profile Vitals Plot — template_vitals","text":"dataname (character) analysis data used teal module. paramcd (character) name parameter code variable. paramcd_levels (character) vector levels paramcd. xaxis (character) name time variable put x-axis. aval Please use aval_var argument instead. aval_var (character) name analysis value variable. patient_id (character) patient ID. font_size (numeric) font size value. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\").","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/template_vitals.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Template: Patient Profile Vitals Plot — template_vitals","text":"list expressions generate table plot object.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_gee.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"module produces analysis table using Generalized Estimating Equations (GEE).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_gee.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"","code":"tm_a_gee( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), aval_var, id_var, arm_var, visit_var, cov_var, arm_ref_comp = NULL, paramcd, conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_gee.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. id_var (teal.transform::choices_selected()) object specifying variable name subject id. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. visit_var (teal.transform::choices_selected()) object available choices preselected option variable names can used visit variable. Must factor dataname. cov_var (teal.transform::choices_selected()) object available choices preselected option covariates variables. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_gee.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_gee.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"module generates following objects, can modified place using decorators: table (ElementaryTable - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_gee.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_gee.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Generalized Estimating Equations (GEE) analysis — tm_a_gee","text":"","code":"library(dplyr) #> #> Attaching package: ‘dplyr’ #> The following object is masked from ‘package:testthat’: #> #> matches #> The following objects are masked from ‘package:stats’: #> #> filter, lag #> The following objects are masked from ‘package:base’: #> #> intersect, setdiff, setequal, union data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADQS <- tmc_ex_adqs %>% filter(ABLFL != \"Y\" & ABLFL2 != \"Y\") %>% mutate( AVISIT = as.factor(AVISIT), AVISITN = rank(AVISITN) %>% as.factor() %>% as.numeric() %>% as.factor(), AVALBIN = AVAL < 50 # Just as an example to get a binary endpoint. ) %>% droplevels() }) join_keys(data) <- default_cdisc_join_keys[names(data)] app <- init( data = data, modules = modules( tm_a_gee( label = \"GEE\", dataname = \"ADQS\", aval_var = choices_selected(\"AVALBIN\", fixed = TRUE), id_var = choices_selected(c(\"USUBJID\", \"SUBJID\"), \"USUBJID\"), arm_var = choices_selected(c(\"ARM\", \"ARMCD\"), \"ARM\"), visit_var = choices_selected(c(\"AVISIT\", \"AVISITN\"), \"AVISIT\"), paramcd = choices_selected( choices = value_choices(data[[\"ADQS\"]], \"PARAMCD\", \"PARAM\"), selected = \"FKSI-FWB\" ), cov_var = choices_selected(c(\"BASE\", \"AGE\", \"SEX\", \"BASE:AVISIT\"), NULL) ) ) ) #> Initializing tm_a_gee (prototype) #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_mmrm.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"module produces analysis tables plots Mixed Model Repeated Measurements.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_mmrm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"","code":"tm_a_mmrm( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), aval_var, id_var, arm_var, visit_var, cov_var, arm_ref_comp = NULL, paramcd, method = teal.transform::choices_selected(c(\"Satterthwaite\", \"Kenward-Roger\", \"Kenward-Roger-Linear\"), \"Satterthwaite\", keep_order = TRUE), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), plot_height = c(700L, 200L, 2000L), plot_width = NULL, total_label = default_total_label(), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_mmrm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. id_var (teal.transform::choices_selected()) object specifying variable name subject id. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. visit_var (teal.transform::choices_selected()) object available choices preselected option variable names can used visit variable. Must factor dataname. cov_var (teal.transform::choices_selected()) object available choices preselected option covariates variables. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. method (teal.transform::choices_selected()) object available choices pre-selected option adjustment method. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings plots named list ggplot2_args objects plot-specific settings. List names match following: c(\"default\", \"lsmeans\", \"diagnostic\"). argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see help vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_mmrm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_mmrm.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"ordering input data sets can lead slightly different numerical results different convergence behavior. known observation used package lme4. However, convergence achieved, results reliable numerical precision.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_mmrm.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"module generates following objects, can modified place using decorators: lsmeans_plot (ggplot2) diagnostic_plot (TableTree- output rtables::build_table) lsmeans_table (TableTree- output rtables::build_table) covariance_table (TableTree- output rtables::build_table) fixed_effects_table (TableTree- output rtables::build_table) diagnostic_table (TableTree- output rtables::build_table) Decorators can applied outputs specific objects using named list teal_transform_module objects. \"default\" name reserved decorators applied outputs. See code snippet :","code":"tm_a_mrmm( ..., # arguments for module decorators = list( default = list(teal_transform_module(...)), # applied to all outputs lsmeans_plot = list(teal_transform_module(...)) # applied only to `lsmeans_plot` output diagnostic_plot = list(teal_transform_module(...)) # applied only to `diagnostic_plot` output lsmeans_table = list(teal_transform_module(...)) # applied only to `lsmeans_table` output covariance_table = list(teal_transform_module(...)) # applied only to `covariance_table` output fixed_effects_table = list(teal_transform_module(...)) # applied only to `fixed_effects_table` output diagnostic_table = list(teal_transform_module(...)) # applied only to `diagnostic_table` output ) )"},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_mmrm.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_a_mmrm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Mixed Model Repeated Measurements (MMRM) Analysis — tm_a_mmrm","text":"","code":"library(dplyr) arm_ref_comp <- list( ARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ) ) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADQS <- tmc_ex_adqs %>% filter(ABLFL != \"Y\" & ABLFL2 != \"Y\") %>% filter(AVISIT %in% c(\"WEEK 1 DAY 8\", \"WEEK 2 DAY 15\", \"WEEK 3 DAY 22\")) %>% mutate( AVISIT = as.factor(AVISIT), AVISITN = rank(AVISITN) %>% as.factor() %>% as.numeric() %>% as.factor() #' making consecutive numeric factor ) }) join_keys(data) <- default_cdisc_join_keys[names(data)] app <- init( data = data, modules = modules( tm_a_mmrm( label = \"MMRM\", dataname = \"ADQS\", aval_var = choices_selected(c(\"AVAL\", \"CHG\"), \"AVAL\"), id_var = choices_selected(c(\"USUBJID\", \"SUBJID\"), \"USUBJID\"), arm_var = choices_selected(c(\"ARM\", \"ARMCD\"), \"ARM\"), visit_var = choices_selected(c(\"AVISIT\", \"AVISITN\"), \"AVISIT\"), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( choices = value_choices(data[[\"ADQS\"]], \"PARAMCD\", \"PARAM\"), selected = \"FKSI-FWB\" ), cov_var = choices_selected(c(\"BASE\", \"AGE\", \"SEX\", \"BASE:AVISIT\"), NULL) ) ) ) #> Initializing tm_a_mmrm #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_barchart_simple.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"module produces ggplot2::ggplot() type bar chart summary table counts per category.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_barchart_simple.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"","code":"tm_g_barchart_simple( x = NULL, fill = NULL, x_facet = NULL, y_facet = NULL, label = \"Count Barchart\", plot_options = NULL, plot_height = c(600L, 200L, 2000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_barchart_simple.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"x (data_extract_spec) variable x-axis. fill (data_extract_spec) grouping variable determine bar colors. x_facet (data_extract_spec) row-wise faceting groups. y_facet (data_extract_spec) column-wise faceting groups. label (character) menu item label module teal app. plot_options (list) list plot options. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_barchart_simple.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_barchart_simple.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"Categories can defined four levels deep defined x, fill, x_facet, y_facet parameters. parameters set NULL (default) ignored.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_barchart_simple.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_barchart_simple.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_barchart_simple.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Simple Bar Chart and Table of Counts per Category — tm_g_barchart_simple","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl %>% mutate(ITTFL = factor(\"Y\") %>% with_label(\"Intent-To-Treat Population Flag\")) ADAE <- tmc_ex_adae %>% filter(!((AETOXGR == 1) & (AESEV == \"MILD\") & (ARM == \"A: Drug X\"))) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADAE <- data[[\"ADAE\"]] app <- init( data = data, modules = modules( tm_g_barchart_simple( label = \"ADAE Analysis\", x = data_extract_spec( dataname = \"ADSL\", select = select_spec( choices = variable_choices( ADSL, c( \"ARM\", \"ACTARM\", \"SEX\", \"RACE\", \"ITTFL\", \"SAFFL\", \"STRATA2\" ) ), selected = \"ACTARM\", multiple = FALSE ) ), fill = list( data_extract_spec( dataname = \"ADSL\", select = select_spec( choices = variable_choices( ADSL, c( \"ARM\", \"ACTARM\", \"SEX\", \"RACE\", \"ITTFL\", \"SAFFL\", \"STRATA2\" ) ), selected = \"SEX\", multiple = FALSE ) ), data_extract_spec( dataname = \"ADAE\", select = select_spec( choices = variable_choices(ADAE, c(\"AETOXGR\", \"AESEV\", \"AESER\")), selected = NULL, multiple = FALSE ) ) ), x_facet = list( data_extract_spec( dataname = \"ADAE\", select = select_spec( choices = variable_choices(ADAE, c(\"AETOXGR\", \"AESEV\", \"AESER\")), selected = \"AETOXGR\", multiple = FALSE ) ), data_extract_spec( dataname = \"ADSL\", select = select_spec( choices = variable_choices( ADSL, c( \"ARM\", \"ACTARM\", \"SEX\", \"RACE\", \"ITTFL\", \"SAFFL\", \"STRATA2\" ) ), selected = NULL, multiple = FALSE ) ) ), y_facet = list( data_extract_spec( dataname = \"ADAE\", select = select_spec( choices = variable_choices(ADAE, c(\"AETOXGR\", \"AESEV\", \"AESER\")), selected = \"AESEV\", multiple = FALSE ) ), data_extract_spec( dataname = \"ADSL\", select = select_spec( choices = variable_choices( ADSL, c( \"ARM\", \"ACTARM\", \"SEX\", \"RACE\", \"ITTFL\", \"SAFFL\", \"STRATA2\" ) ), selected = NULL, multiple = FALSE ) ) ) ) ) ) #> Initializing tm_g_barchart_simple #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ci.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Confidence Interval Plot — tm_g_ci","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"module produces ggplot2::ggplot() type confidence interval plot consistent TLG Catalog template CIG01 available .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ci.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"","code":"tm_g_ci( label, x_var, y_var, color, stat = c(\"mean\", \"median\"), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), plot_height = c(700L, 200L, 2000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ci.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"label (character) menu item label module teal app. x_var (character) name treatment variable put x-axis. y_var (character) name response variable put y-axis. color (data_extract_spec) group variable used determine plot colors, shapes, line types. stat (character) statistic plot. Options \"mean\" \"median\". conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ci.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ci.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ci.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ci.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Confidence Interval Plot — tm_g_ci","text":"","code":"library(nestcolor) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_g_ci( label = \"Confidence Interval Plot\", x_var = data_extract_spec( dataname = \"ADSL\", select = select_spec( choices = c(\"ARMCD\", \"BMRKR2\"), selected = c(\"ARMCD\"), multiple = FALSE, fixed = FALSE ) ), y_var = data_extract_spec( dataname = \"ADLB\", filter = list( filter_spec( vars = \"PARAMCD\", choices = levels(ADLB$PARAMCD), selected = levels(ADLB$PARAMCD)[1], multiple = FALSE, label = \"Select lab:\" ), filter_spec( vars = \"AVISIT\", choices = levels(ADLB$AVISIT), selected = levels(ADLB$AVISIT)[1], multiple = FALSE, label = \"Select visit:\" ) ), select = select_spec( label = \"Analyzed Value\", choices = c(\"AVAL\", \"CHG\"), selected = \"AVAL\", multiple = FALSE, fixed = FALSE ) ), color = data_extract_spec( dataname = \"ADSL\", select = select_spec( label = \"Color by variable\", choices = c(\"SEX\", \"STRATA1\", \"STRATA2\"), selected = c(\"STRATA1\"), multiple = FALSE, fixed = FALSE ) ) ) ) ) #> Initializing tm_g_ci #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_rsp.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Forest Response Plot — tm_g_forest_rsp","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"module produces grid-style forest plot response data ADaM structure.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_rsp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"","code":"tm_g_forest_rsp( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, arm_ref_comp = NULL, paramcd, aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALC\"), \"AVALC\", fixed = TRUE), subgroup_var, strata_var, stats = c(\"n_tot\", \"n\", \"n_rsp\", \"prop\", \"or\", \"ci\"), riskdiff = NULL, fixed_symbol_size = TRUE, conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), default_responses = c(\"CR\", \"PR\", \"Y\", \"Complete Response (CR)\", \"Partial Response (PR)\"), plot_height = c(500L, 200L, 2000L), plot_width = c(1500L, 800L, 3000L), rel_width_forest = c(25L, 0L, 100L), font_size = c(15L, 1L, 30L), pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_rsp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. subgroup_var (teal.transform::choices_selected()) object available choices preselected option variable names can used default subgroups. strata_var (teal.transform::choices_selected()) names variables stratified analysis. stats (character) names statistics reported among: n: Total number observations per group. n_rsp: Number responders per group. prop: Proportion responders. n_tot: Total number observations. : Odds ratio. ci : Confidence interval odds ratio. pval: p-value effect. Note, statistics n_tot, , ci required. riskdiff (list) risk (proportion) difference column added, list settings apply within column. See tern::control_riskdiff() details. NULL, risk difference column added. fixed_symbol_size (logical) (TRUE), symbol size used plotting estimate. Otherwise, symbol size proportional sample size subgroup. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). default_responses (list character) defines default codes response variable module per value paramcd. passed vector transmitted paramcd values. passed list must named contain arrays, name corresponding single value paramcd. array may contain default response values named arrays rsp default selected response values levels default level choices. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. rel_width_forest (proportion) proportion total width allocate forest plot. Relative width table 1 - rel_width_forest. as_list = TRUE, parameter ignored. font_size (numeric(1)) font size. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. module, argument accept ggplot2_args object labs list following child elements: title, caption. elements taken account. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_rsp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_rsp.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_rsp.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_rsp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Forest Response Plot — tm_g_forest_rsp","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADRS <- tmc_ex_adrs %>% mutate(AVALC = d_onco_rsp_label(AVALC) %>% with_label(\"Character Result/Finding\")) %>% filter(PARAMCD != \"OVRINV\" | AVISIT == \"FOLLOW UP\") }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADRS <- data[[\"ADRS\"]] arm_ref_comp <- list( ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ), ARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ) ) app <- init( data = data, modules = modules( tm_g_forest_rsp( label = \"Forest Response\", dataname = \"ADRS\", arm_var = choices_selected( variable_choices(ADSL, c(\"ARM\", \"ARMCD\")), \"ARMCD\" ), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( value_choices(ADRS, \"PARAMCD\", \"PARAM\"), \"INVET\" ), subgroup_var = choices_selected( variable_choices(ADSL, names(ADSL)), c(\"BMRKR2\", \"SEX\") ), strata_var = choices_selected( variable_choices(ADSL, c(\"STRATA1\", \"STRATA2\")), \"STRATA2\" ), plot_height = c(600L, 200L, 2000L), default_responses = list( BESRSPI = list( rsp = c(\"Stable Disease (SD)\", \"Not Evaluable (NE)\"), levels = c( \"Complete Response (CR)\", \"Partial Response (PR)\", \"Stable Disease (SD)\", \"Progressive Disease (PD)\", \"Not Evaluable (NE)\" ) ), INVET = list( rsp = c(\"Complete Response (CR)\", \"Partial Response (PR)\"), levels = c( \"Complete Response (CR)\", \"Not Evaluable (NE)\", \"Partial Response (PR)\", \"Progressive Disease (PD)\", \"Stable Disease (SD)\" ) ), OVRINV = list( rsp = c(\"Progressive Disease (PD)\", \"Stable Disease (SD)\"), levels = c(\"Progressive Disease (PD)\", \"Stable Disease (SD)\", \"Not Evaluable (NE)\") ) ) ) ) ) #> Initializing tm_g_forest_rsp #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_tte.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Forest Survival Plot — tm_g_forest_tte","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"module produces grid-style forest plot time--event data ADaM structure.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_tte.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"","code":"tm_g_forest_tte( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, arm_ref_comp = NULL, subgroup_var, paramcd, strata_var, aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVAL\"), \"AVAL\", fixed = TRUE), cnsr_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"CNSR\"), \"CNSR\", fixed = TRUE), stats = c(\"n_tot_events\", \"n_events\", \"median\", \"hr\", \"ci\"), riskdiff = NULL, conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), time_unit_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALU\"), \"AVALU\", fixed = TRUE), fixed_symbol_size = TRUE, plot_height = c(500L, 200L, 2000L), plot_width = c(1500L, 800L, 3000L), rel_width_forest = c(25L, 0L, 100L), font_size = c(15L, 1L, 30L), pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_tte.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. subgroup_var (teal.transform::choices_selected()) object available choices preselected option variable names can used default subgroups. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. strata_var (teal.transform::choices_selected()) names variables stratified analysis. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. cnsr_var (teal.transform::choices_selected()) object available choices preselected option censoring variable. stats (character) names statistics reported among: n_tot_events: Total number events per group. n_events: Number events per group. n_tot: Total number observations per group. n: Number observations per group. median: Median survival time. hr: Hazard ratio. ci: Confidence interval hazard ratio. pval: p-value effect. Note, one statistics n_tot n_tot_events, well hr ci required. riskdiff (list) risk (proportion) difference column added, list settings apply within column. See tern::control_riskdiff() details. NULL, risk difference column added. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). time_unit_var (teal.transform::choices_selected()) object available choices pre-selected option time unit variable. fixed_symbol_size (logical) (TRUE), symbol size used plotting estimate. Otherwise, symbol size proportional sample size subgroup. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. rel_width_forest (proportion) proportion total width allocate forest plot. Relative width table 1 - rel_width_forest. as_list = TRUE, parameter ignored. font_size (numeric(1)) font size. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_tte.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_tte.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_tte.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_forest_tte.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Forest Survival Plot — tm_g_forest_tte","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADTTE <- tmc_ex_adtte ADSL$RACE <- droplevels(ADSL$RACE) %>% with_label(\"Race\") }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADTTE <- data[[\"ADTTE\"]] arm_ref_comp <- list( ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ), ARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ) ) app <- init( data = data, modules = modules( tm_g_forest_tte( label = \"Forest Survival\", dataname = \"ADTTE\", arm_var = choices_selected( variable_choices(ADSL, c(\"ARM\", \"ARMCD\")), \"ARMCD\" ), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( value_choices(ADTTE, \"PARAMCD\", \"PARAM\"), \"OS\" ), subgroup_var = choices_selected( variable_choices(ADSL, names(ADSL)), c(\"BMRKR2\", \"SEX\") ), strata_var = choices_selected( variable_choices(ADSL, c(\"STRATA1\", \"STRATA2\")), \"STRATA2\" ) ) ) ) #> Initializing tm_g_forest_tte #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ipp.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Individual Patient Plots — tm_g_ipp","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"module produces ggplot2::ggplot() type individual patient plots display trends parameter values time patient, using data ADaM structure.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ipp.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"","code":"tm_g_ipp( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, paramcd, id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"USUBJID\"), \"USUBJID\", fixed = TRUE), visit_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVISIT\"), \"AVISIT\", fixed = TRUE), aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVAL\"), \"AVAL\", fixed = TRUE), avalu_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALU\"), \"AVALU\", fixed = TRUE), base_var = lifecycle::deprecated(), baseline_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"BASE\"), \"BASE\", fixed = TRUE), add_baseline_hline = FALSE, separate_by_obs = FALSE, suppress_legend = FALSE, add_avalu = TRUE, plot_height = c(1200L, 400L, 5000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ipp.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable values can used arm variable. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. id_var (teal.transform::choices_selected()) object specifying variable name subject id. visit_var (teal.transform::choices_selected()) object available choices preselected option variable names can used visit variable. Must factor dataname. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. avalu_var (teal.transform::choices_selected()) object available choices preselected option analysis unit variable. base_var Please use baseline_var argument instead. baseline_var (teal.transform::choices_selected()) object available choices preselected option variable values can used baseline_var. add_baseline_hline (logical) whether horizontal line added plot baseline y-value. separate_by_obs (logical) whether create multi-panel plots. suppress_legend (logical) whether suppress plot legend. add_avalu (logical) whether avalu_first text appended plot title y-axis label. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. module, argument accept ggplot2_args object labs list following child elements: title, subtitle, x, y. elements taken account. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ipp.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ipp.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ipp.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_ipp.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Individual Patient Plots — tm_g_ipp","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl %>% slice(1:20) %>% df_explicit_na() ADLB <- tmc_ex_adlb %>% filter(USUBJID %in% ADSL$USUBJID) %>% df_explicit_na() %>% filter(AVISIT != \"SCREENING\") }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_g_ipp( label = \"Individual Patient Plot\", dataname = \"ADLB\", arm_var = choices_selected( value_choices(ADLB, \"ARMCD\"), \"ARM A\" ), paramcd = choices_selected( value_choices(ADLB, \"PARAMCD\"), \"ALT\" ), aval_var = choices_selected( variable_choices(ADLB, c(\"AVAL\", \"CHG\")), \"AVAL\" ), avalu_var = choices_selected( variable_choices(ADLB, c(\"AVALU\")), \"AVALU\", fixed = TRUE ), id_var = choices_selected( variable_choices(ADLB, c(\"USUBJID\")), \"USUBJID\", fixed = TRUE ), visit_var = choices_selected( variable_choices(ADLB, c(\"AVISIT\")), \"AVISIT\" ), baseline_var = choices_selected( variable_choices(ADLB, c(\"BASE\")), \"BASE\", fixed = TRUE ), add_baseline_hline = FALSE, separate_by_obs = FALSE ) ) ) #> Initializing tm_g_ipp #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_km.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Kaplan-Meier Plot — tm_g_km","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"module produces ggplot-style Kaplan-Meier plot data ADaM structure.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_km.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"","code":"tm_g_km( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, arm_ref_comp = NULL, paramcd, strata_var, facet_var, time_unit_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALU\"), \"AVALU\", fixed = TRUE), aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVAL\"), \"AVAL\", fixed = TRUE), cnsr_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"CNSR\"), \"CNSR\", fixed = TRUE), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), font_size = c(11L, 1L, 30), control_annot_surv_med = control_surv_med_annot(), control_annot_coxph = control_coxph_annot(x = 0.27, y = 0.35, w = 0.3), legend_pos = c(0.9, 0.5), rel_height_plot = c(80L, 0L, 100L), plot_height = c(800L, 400L, 5000L), plot_width = NULL, pre_output = NULL, post_output = NULL, decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_km.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. strata_var (teal.transform::choices_selected()) names variables stratified analysis. facet_var (teal.transform::choices_selected()) object available choices preselected option names variable can used plot faceting. time_unit_var (teal.transform::choices_selected()) object available choices pre-selected option time unit variable. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. cnsr_var (teal.transform::choices_selected()) object available choices preselected option censoring variable. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). font_size (numeric) numeric vector length 3 current, minimum maximum font size values. control_annot_surv_med (list) parameters control position size annotation table added plot annot_surv_med = TRUE, specified using control_surv_med_annot() function. Parameter options : x, y, w, h, fill. See control_surv_med_annot() details. control_annot_coxph (list) parameters control position size annotation table added plot annot_coxph = TRUE, specified using control_coxph_annot() function. Parameter options : x, y, w, h, fill, ref_lbls. See control_coxph_annot() details. legend_pos (numeric(2) NULL) vector containing x- y-coordinates, respectively, legend position relative KM plot area. NULL (default), legend positioned bottom right corner plot, middle right plot needed prevent overlapping. rel_height_plot (proportion) proportion total figure height allocate Kaplan-Meier plot. Relative height patients risk table 1 - rel_height_plot. annot_at_risk = FALSE as_list = TRUE, parameter ignored. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_km.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_km.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_km.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_km.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Kaplan-Meier Plot — tm_g_km","text":"","code":"library(nestcolor) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADTTE <- tmc_ex_adtte }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADTTE <- data[[\"ADTTE\"]] arm_ref_comp <- list( ACTARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ), ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ) ) app <- init( data = data, modules = modules( tm_g_km( label = \"Kaplan-Meier Plot\", dataname = \"ADTTE\", arm_var = choices_selected( variable_choices(ADSL, c(\"ARM\", \"ARMCD\", \"ACTARMCD\")), \"ARM\" ), paramcd = choices_selected( value_choices(ADTTE, \"PARAMCD\", \"PARAM\"), \"OS\" ), arm_ref_comp = arm_ref_comp, strata_var = choices_selected( variable_choices(ADSL, c(\"SEX\", \"BMRKR2\")), \"SEX\" ), facet_var = choices_selected( variable_choices(ADSL, c(\"SEX\", \"BMRKR2\")), NULL ) ) ) ) #> Initializing tm_g_km #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_lineplot.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Line Plot — tm_g_lineplot","title":"teal Module: Line Plot — tm_g_lineplot","text":"module produces ggplot2::ggplot() type line plot, optional summary table, standard ADaM data.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_lineplot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Line Plot — tm_g_lineplot","text":"","code":"tm_g_lineplot( label, dataname, parentname = NULL, strata = lifecycle::deprecated(), group_var = teal.transform::choices_selected(teal.transform::variable_choices(parentname, c(\"ARM\", \"ARMCD\", \"ACTARMCD\")), \"ARM\"), x = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVISIT\"), \"AVISIT\", fixed = TRUE), y = teal.transform::choices_selected(teal.transform::variable_choices(dataname, c(\"AVAL\", \"BASE\", \"CHG\", \"PCHG\")), \"AVAL\"), y_unit = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALU\"), \"AVALU\", fixed = TRUE), paramcd = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"PARAMCD\"), \"PARAMCD\", fixed = TRUE), param = teal.transform::choices_selected(teal.transform::value_choices(dataname, \"PARAMCD\", \"PARAM\"), \"ALT\"), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), interval = \"mean_ci\", mid = \"mean\", whiskers = c(\"mean_ci_lwr\", \"mean_ci_upr\"), table = c(\"n\", \"mean_sd\", \"median\", \"range\"), mid_type = \"pl\", mid_point_size = c(2, 1, 5), table_font_size = c(4, 2, 6), plot_height = c(1000L, 200L, 4000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_lineplot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Line Plot — tm_g_lineplot","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. strata Please use group_var argument instead. group_var (string NA) group variable name. x (string) x-variable name. y (string) y-variable name. y_unit (string NA) y-axis unit variable name. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. param (character) parameter filter data . conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). interval (character NULL) names statistics plotted intervals. statistics indicated interval variable must present object returned sfun, double numeric type vector length two. Set interval = NULL intervals added plot. mid (character NULL) names statistics plotted midpoints. statistics indicated mid variable must present object returned sfun, double numeric type vector length one. whiskers (character) names interval whiskers plotted. Names must match names list element interval returned sfun (e.g. mean_ci_lwr element sfun(x)[[\"mean_ci\"]]). possible specify one whisker , suppress whiskers setting interval = NULL. table (character NULL) names statistics displayed table plot. statistics indicated table variable must present object returned sfun. mid_type (string) controls type mid plot, can point (\"p\"), line (\"l\"), point line (\"pl\"). mid_point_size (numeric(1)) font size mid plot points. table_font_size (numeric(1)) font size text table. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. module, argument accept ggplot2_args object labs list following child elements: title, subtitle, caption, y, lty. elements taken account. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_lineplot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Line Plot — tm_g_lineplot","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_lineplot.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Line Plot — tm_g_lineplot","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_lineplot.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Line Plot — tm_g_lineplot","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_lineplot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Line Plot — tm_g_lineplot","text":"","code":"library(nestcolor) library(dplyr) library(forcats) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb %>% mutate(AVISIT == fct_reorder(AVISIT, AVISITN, min)) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_g_lineplot( label = \"Line Plot\", dataname = \"ADLB\", group_var = choices_selected( variable_choices(ADSL, c(\"ARM\", \"ARMCD\", \"ACTARMCD\")), \"ARM\" ), y = choices_selected( variable_choices(ADLB, c(\"AVAL\", \"BASE\", \"CHG\", \"PCHG\")), \"AVAL\" ), param = choices_selected( value_choices(ADLB, \"PARAMCD\", \"PARAM\"), \"ALT\" ) ) ) ) #> Initializing tm_g_lineplot #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_adverse_events.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"module produces adverse events table ggplot2::ggplot() type plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_adverse_events.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"","code":"tm_g_pp_adverse_events( label, dataname = \"ADAE\", parentname = \"ADSL\", patient_col = \"USUBJID\", aeterm = NULL, tox_grade = NULL, causality = NULL, outcome = NULL, action = NULL, time = NULL, decod = NULL, font_size = c(12L, 12L, 25L), plot_height = c(700L, 200L, 2000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_adverse_events.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. aeterm (teal.transform::choices_selected()) object available choices preselected option AETERM variable dataname. tox_grade (teal.transform::choices_selected()) object available choices preselected option AETOXGR variable dataname. causality (teal.transform::choices_selected()) object available choices preselected option AEREL variable dataname. outcome (teal.transform::choices_selected()) object available choices preselected option AEOUT variable dataname. action (teal.transform::choices_selected()) object available choices preselected option AEACN variable dataname. time (teal.transform::choices_selected()) object available choices preselected option ASTDY variable dataname. decod (teal.transform::choices_selected()) object available choices preselected option AEDECOD variable dataname. font_size (numeric) numeric vector length 3 current, minimum maximum font size values. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_adverse_events.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_adverse_events.html","id":"decorating-modules","dir":"Reference","previous_headings":"","what":"Decorating Modules","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"module generates following objects, can modified place using decorators:: plot (ggplot2) table (listing_df - output rlistings::as_listing) Decorators can applied outputs specific objects using named list teal_transform_module objects. \"default\" name reserved decorators applied outputs. See code snippet : additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":"tm_g_pp_adverse_events( ..., # arguments for module decorators = list( default = list(teal_transform_module(...)), # applied to all outputs plot = list(teal_transform_module(...)), # applied only to `plot` output table = list(teal_transform_module(...)) # applied only to `table` output ) )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_adverse_events.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_adverse_events.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Adverse Events Table and Plot — tm_g_pp_adverse_events","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADAE <- tmc_ex_adae ADSL <- tmc_ex_adsl %>% filter(USUBJID %in% ADAE$USUBJID) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADAE <- data[[\"ADAE\"]] app <- init( data = data, modules = modules( tm_g_pp_adverse_events( label = \"Adverse Events\", dataname = \"ADAE\", parentname = \"ADSL\", patient_col = \"USUBJID\", plot_height = c(600L, 200L, 2000L), aeterm = choices_selected( choices = variable_choices(ADAE, \"AETERM\"), selected = \"AETERM\" ), tox_grade = choices_selected( choices = variable_choices(ADAE, \"AETOXGR\"), selected = \"AETOXGR\" ), causality = choices_selected( choices = variable_choices(ADAE, \"AEREL\"), selected = \"AEREL\" ), outcome = choices_selected( choices = variable_choices(ADAE, \"AEOUT\"), selected = \"AEOUT\" ), action = choices_selected( choices = variable_choices(ADAE, \"AEACN\"), selected = \"AEACN\" ), time = choices_selected( choices = variable_choices(ADAE, \"ASTDY\"), selected = \"ASTDY\" ), decod = NULL ) ) ) #> Initializing tm_g_pp_adverse_events #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_patient_timeline.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"module produces patient profile timeline ggplot2::ggplot() type plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_patient_timeline.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"","code":"tm_g_pp_patient_timeline( label, dataname_adcm = \"ADCM\", dataname_adae = \"ADAE\", parentname = \"ADSL\", patient_col = \"USUBJID\", aeterm = NULL, cmdecod = NULL, aetime_start = NULL, aetime_end = NULL, dstime_start = NULL, dstime_end = NULL, aerelday_start = NULL, aerelday_end = NULL, dsrelday_start = NULL, dsrelday_end = NULL, font_size = c(12L, 12L, 25L), plot_height = c(700L, 200L, 2000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_patient_timeline.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"label (character) menu item label module teal app. dataname_adcm (character) name ADCM dataset equivalent. dataname_adae (character) name ADAE dataset equivalent. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. aeterm (teal.transform::choices_selected()) object available choices preselected option AETERM variable dataname. cmdecod (teal.transform::choices_selected()) object available choices preselected option CMDECOD variable dataname_adcm. aetime_start (teal.transform::choices_selected()) object available choices preselected option ASTDTM variable dataname_adae. aetime_end (teal.transform::choices_selected()) object available choices preselected option AENDTM variable dataname_adae. dstime_start (teal.transform::choices_selected()) object available choices preselected option CMASTDTM variable dataname_adcm. dstime_end (teal.transform::choices_selected()) object available choices preselected option CMAENDTM variable dataname_adcm. aerelday_start (teal.transform::choices_selected()) object available choices preselected option ASTDY variable dataname_adae. aerelday_end (teal.transform::choices_selected()) object available choices preselected option AENDY variable dataname_adae. dsrelday_start (teal.transform::choices_selected()) object available choices preselected option ASTDY variable dataname_adcm. dsrelday_end (teal.transform::choices_selected()) object available choices preselected option AENDY variable dataname_adcm. font_size (numeric) numeric vector length 3 current, minimum maximum font size values. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_patient_timeline.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_patient_timeline.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_patient_timeline.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_patient_timeline.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Timeline Plot — tm_g_pp_patient_timeline","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADAE <- tmc_ex_adae ADSL <- tmc_ex_adsl %>% filter(USUBJID %in% ADAE$USUBJID) ADCM <- tmc_ex_adcm %>% mutate( CMSTDY = case_when( CMCAT == \"medcl B\" ~ 20, CMCAT == \"medcl C\" ~ 150, TRUE ~ 1 ) %>% with_label(\"Study Day of Start of Medication\"), CMENDY = case_when( CMCAT == \"medcl B\" ~ 700, CMCAT == \"medcl C\" ~ 1000, TRUE ~ 500 ) %>% with_label(\"Study Day of End of Medication\"), CMASTDTM = ASTDTM, CMAENDTM = AENDTM ) }) join_keys(data) <- default_cdisc_join_keys[c(\"ADSL\", \"ADAE\", \"ADCM\")] adcm_keys <- c(\"STUDYID\", \"USUBJID\", \"ASTDTM\", \"CMSEQ\", \"ATC1\", \"ATC2\", \"ATC3\", \"ATC4\") join_keys(data)[\"ADCM\", \"ADCM\"] <- adcm_keys join_keys(data)[\"ADAE\", \"ADCM\"] <- c(\"STUDYID\", \"USUBJID\") app <- init( data = data, modules = modules( tm_g_pp_patient_timeline( label = \"Patient Timeline\", dataname_adae = \"ADAE\", dataname_adcm = \"ADCM\", parentname = \"ADSL\", patient_col = \"USUBJID\", plot_height = c(600L, 200L, 2000L), cmdecod = choices_selected( choices = variable_choices(data[[\"ADCM\"]], \"CMDECOD\"), selected = \"CMDECOD\", ), aeterm = choices_selected( choices = variable_choices(data[[\"ADAE\"]], \"AETERM\"), selected = c(\"AETERM\") ), aetime_start = choices_selected( choices = variable_choices(data[[\"ADAE\"]], \"ASTDTM\"), selected = c(\"ASTDTM\") ), aetime_end = choices_selected( choices = variable_choices(data[[\"ADAE\"]], \"AENDTM\"), selected = c(\"AENDTM\") ), dstime_start = choices_selected( choices = variable_choices(data[[\"ADCM\"]], \"CMASTDTM\"), selected = c(\"CMASTDTM\") ), dstime_end = choices_selected( choices = variable_choices(data[[\"ADCM\"]], \"CMAENDTM\"), selected = c(\"CMAENDTM\") ), aerelday_start = choices_selected( choices = variable_choices(data[[\"ADAE\"]], \"ASTDY\"), selected = c(\"ASTDY\") ), aerelday_end = choices_selected( choices = variable_choices(data[[\"ADAE\"]], \"AENDY\"), selected = c(\"AENDY\") ), dsrelday_start = choices_selected( choices = variable_choices(data[[\"ADCM\"]], \"ASTDY\"), selected = c(\"ASTDY\") ), dsrelday_end = choices_selected( choices = variable_choices(data[[\"ADCM\"]], \"AENDY\"), selected = c(\"AENDY\") ) ) ) ) #> Initializing tm_g_pp_patient_timeline #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_therapy.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"module produces patient profile therapy table ggplot2::ggplot() type plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_therapy.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"","code":"tm_g_pp_therapy( label, dataname = \"ADCM\", parentname = \"ADSL\", patient_col = \"USUBJID\", atirel = NULL, cmdecod = NULL, cmindc = NULL, cmdose = NULL, cmtrt = NULL, cmdosu = NULL, cmroute = NULL, cmdosfrq = NULL, cmstdy = NULL, cmendy = NULL, font_size = c(12L, 12L, 25L), plot_height = c(700L, 200L, 2000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_therapy.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. atirel (teal.transform::choices_selected()) object available choices preselected option ATIREL variable dataname. cmdecod (teal.transform::choices_selected()) object available choices preselected option CMDECOD variable dataname. cmindc (teal.transform::choices_selected()) object available choices preselected option CMINDC variable dataname. cmdose (teal.transform::choices_selected()) object available choices preselected option CMDOSE variable dataname. cmtrt (teal.transform::choices_selected()) object available choices preselected option CMTRT variable dataname. cmdosu (teal.transform::choices_selected()) object available choices preselected option CMDOSU variable dataname. cmroute (teal.transform::choices_selected()) object available choices preselected option CMROUTE variable dataname. cmdosfrq (teal.transform::choices_selected()) object available choices preselected option CMDOSFRQ variable dataname. cmstdy (teal.transform::choices_selected()) object available choices preselected option CMSTDY variable dataname. cmendy (teal.transform::choices_selected()) object available choices preselected option CMENDY variable dataname. font_size (numeric) numeric vector length 3 current, minimum maximum font size values. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_therapy.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_therapy.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"module generates following objects, can modified place using decorators:: plot (ggplot2) table (listing_df - output rlistings::as_listing) Decorators can applied outputs specific objects using named list teal_transform_module objects. \"default\" name reserved decorators applied outputs. See code snippet : additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":"tm_g_pp_therapy( ..., # arguments for module decorators = list( default = list(teal_transform_module(...)), # applied to all outputs plot = list(teal_transform_module(...)), # applied only to `plot` output table = list(teal_transform_module(...)) # applied only to `table` output ) )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_therapy.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_therapy.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Therapy Table and Plot — tm_g_pp_therapy","text":"","code":"library(nestcolor) library(dplyr) data <- teal_data() data <- within(data, { ADCM <- tmc_ex_adcm ADSL <- tmc_ex_adsl %>% filter(USUBJID %in% ADCM$USUBJID) ADCM$CMASTDTM <- ADCM$ASTDTM ADCM$CMAENDTM <- ADCM$AENDTM }) join_keys(data) <- default_cdisc_join_keys[c(\"ADSL\", \"ADCM\")] adcm_keys <- c(\"STUDYID\", \"USUBJID\", \"ASTDTM\", \"CMSEQ\", \"ATC1\", \"ATC2\", \"ATC3\", \"ATC4\") join_keys(data)[\"ADCM\", \"ADCM\"] <- adcm_keys ADSL <- data[[\"ADSL\"]] ADCM <- data[[\"ADCM\"]] app <- init( data = data, modules = modules( tm_g_pp_therapy( label = \"Therapy\", dataname = \"ADCM\", parentname = \"ADSL\", patient_col = \"USUBJID\", plot_height = c(600L, 200L, 2000L), atirel = choices_selected( choices = variable_choices(ADCM, \"ATIREL\"), selected = c(\"ATIREL\") ), cmdecod = choices_selected( choices = variable_choices(ADCM, \"CMDECOD\"), selected = \"CMDECOD\" ), cmindc = choices_selected( choices = variable_choices(ADCM, \"CMINDC\"), selected = \"CMINDC\" ), cmdose = choices_selected( choices = variable_choices(ADCM, \"CMDOSE\"), selected = \"CMDOSE\" ), cmtrt = choices_selected( choices = variable_choices(ADCM, \"CMTRT\"), selected = \"CMTRT\" ), cmdosu = choices_selected( choices = variable_choices(ADCM, \"CMDOSU\"), selected = c(\"CMDOSU\") ), cmroute = choices_selected( choices = variable_choices(ADCM, \"CMROUTE\"), selected = \"CMROUTE\" ), cmdosfrq = choices_selected( choices = variable_choices(ADCM, \"CMDOSFRQ\"), selected = \"CMDOSFRQ\" ), cmstdy = choices_selected( choices = variable_choices(ADCM, \"ASTDY\"), selected = \"ASTDY\" ), cmendy = choices_selected( choices = variable_choices(ADCM, \"AENDY\"), selected = \"AENDY\" ) ) ) ) #> Initializing tm_g_pp_therapy #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_vitals.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"module produces patient profile vitals ggplot2::ggplot() type plot using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_vitals.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"","code":"tm_g_pp_vitals( label, dataname = \"ADVS\", parentname = \"ADSL\", patient_col = \"USUBJID\", paramcd = NULL, aval = lifecycle::deprecated(), aval_var = NULL, xaxis = NULL, font_size = c(12L, 12L, 25L), plot_height = c(700L, 200L, 2000L), plot_width = NULL, pre_output = NULL, post_output = NULL, ggplot2_args = teal.widgets::ggplot2_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_vitals.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. aval Please use aval_var argument instead. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. xaxis (teal.transform::choices_selected()) object available choices preselected option time variable dataname put plot x-axis. font_size (numeric) numeric vector length 3 current, minimum maximum font size values. plot_height (numeric) optional vector length three c(value, min, max). Specifies height main plot renders slider plot interactively adjust plot height. plot_width (numeric) optional vector length three c(value, min, max). Specifies width main plot renders slider plot interactively adjust plot width. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. ggplot2_args (ggplot2_args) optional object created teal.widgets::ggplot2_args() settings module plot. argument merged option teal.ggplot2_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-ggplot2-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_vitals.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_vitals.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"plot supports horizontal lines following 6 PARAMCD levels present dataname: \"SYSBP\", \"DIABP\", \"TEMP\", \"RESP\", \"OXYSAT\".","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_vitals.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"module generates following objects, can modified place using decorators: plot (ggplot2) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_vitals.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_g_pp_vitals.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Vitals Plot — tm_g_pp_vitals","text":"","code":"library(nestcolor) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADVS <- tmc_ex_advs }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADVS <- data[[\"ADVS\"]] app <- init( data = data, modules = modules( tm_g_pp_vitals( label = \"Vitals\", dataname = \"ADVS\", parentname = \"ADSL\", patient_col = \"USUBJID\", plot_height = c(600L, 200L, 2000L), paramcd = choices_selected( choices = variable_choices(ADVS, \"PARAMCD\"), selected = \"PARAMCD\" ), xaxis = choices_selected( choices = variable_choices(ADVS, \"ADY\"), selected = \"ADY\" ), aval_var = choices_selected( choices = variable_choices(ADVS, \"AVAL\"), selected = \"AVAL\" ) ) ) ) #> Initializing tm_g_pp_vitals #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Abnormality Summary Table — tm_t_abnormality","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"module produces table summarize abnormality.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"","code":"tm_t_abnormality( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, by_vars, grade, abnormal = list(low = c(\"LOW\", \"LOW LOW\"), high = c(\"HIGH\", \"HIGH HIGH\")), id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"USUBJID\"), selected = \"USUBJID\", fixed = TRUE), baseline_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"BNRIND\"), selected = \"BNRIND\", fixed = TRUE), treatment_flag_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"ONTRTFL\"), selected = \"ONTRTFL\", fixed = TRUE), treatment_flag = teal.transform::choices_selected(\"Y\"), add_total = TRUE, total_label = default_total_label(), exclude_base_abn = FALSE, drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, na_level = default_na_str(), basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. by_vars (teal.transform::choices_selected()) object available choices preselected option variable names used split summary rows. grade (teal.transform::choices_selected()) object available choices preselected option variable names can used specify abnormality grade. Variable must factor. abnormal (named list) defined user indicate abnormalities displayed. id_var (teal.transform::choices_selected()) object specifying variable name subject id. baseline_var (teal.transform::choices_selected()) variable baseline abnormality grade. treatment_flag_var (teal.transform::choices_selected()) treatment flag variable. treatment_flag (teal.transform::choices_selected()) value indicating treatment records treatment_flag_var. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). exclude_base_abn (logical) whether exclude patients abnormal values baseline. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. na_level (character) NA level input dataset, default \"\". basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"Patients abnormality baseline treatment visit can excluded accordance GDSR specifications using exclude_base_abn.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"module generates following objects, can modified place using decorators: table (ElementaryTable - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Abnormality Summary Table — tm_t_abnormality","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb %>% mutate( ONTRTFL = case_when( AVISIT %in% c(\"SCREENING\", \"BASELINE\") ~ \"\", TRUE ~ \"Y\" ) %>% with_label(\"On Treatment Record Flag\") ) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_t_abnormality( label = \"Abnormality Table\", dataname = \"ADLB\", arm_var = choices_selected( choices = variable_choices(ADSL, subset = c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), add_total = FALSE, by_vars = choices_selected( choices = variable_choices(ADLB, subset = c(\"LBCAT\", \"PARAM\", \"AVISIT\")), selected = c(\"LBCAT\", \"PARAM\"), keep_order = TRUE ), baseline_var = choices_selected( variable_choices(ADLB, subset = \"BNRIND\"), selected = \"BNRIND\", fixed = TRUE ), grade = choices_selected( choices = variable_choices(ADLB, subset = \"ANRIND\"), selected = \"ANRIND\", fixed = TRUE ), abnormal = list(low = \"LOW\", high = \"HIGH\"), exclude_base_abn = FALSE ) ) ) #> Initializing tm_t_abnormality #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality_by_worst_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"module produces table summarize laboratory test results highest grade post-baseline","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality_by_worst_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"","code":"tm_t_abnormality_by_worst_grade( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"USUBJID\"), selected = \"USUBJID\", fixed = TRUE), paramcd, atoxgr_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"ATOXGR\"), selected = \"ATOXGR\", fixed = TRUE), worst_high_flag_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"WGRHIFL\"), selected = \"WGRHIFL\", fixed = TRUE), worst_low_flag_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"WGRLOFL\"), selected = \"WGRLOFL\", fixed = TRUE), worst_flag_indicator = teal.transform::choices_selected(\"Y\"), add_total = TRUE, total_label = default_total_label(), drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality_by_worst_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. id_var (teal.transform::choices_selected()) object specifying variable name subject id. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. atoxgr_var (teal.transform::choices_selected()) object available choices preselected option variable names can used Analysis Toxicity Grade. worst_high_flag_var (teal.transform::choices_selected()) object available choices preselected option variable names can used Worst High Grade flag. worst_low_flag_var (teal.transform::choices_selected()) object available choices preselected option variable names can used Worst Low Grade flag. worst_flag_indicator (teal.transform::choices_selected()) value indicating worst grade. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality_by_worst_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality_by_worst_grade.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"module generates following objects, can modified place using decorators: table (ElementaryTable - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality_by_worst_grade.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_abnormality_by_worst_grade.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Laboratory test results with highest grade post-baseline — tm_t_abnormality_by_worst_grade","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb %>% filter(!AVISIT %in% c(\"SCREENING\", \"BASELINE\")) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_t_abnormality_by_worst_grade( label = \"Laboratory Test Results with Highest Grade Post-Baseline\", dataname = \"ADLB\", arm_var = choices_selected( choices = variable_choices(ADSL, subset = c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), paramcd = choices_selected( choices = value_choices(ADLB, \"PARAMCD\", \"PARAM\"), selected = c(\"ALT\", \"CRP\", \"IGA\") ), add_total = FALSE ) ), filter = teal_slices( teal_slice(\"ADSL\", \"SAFFL\", selected = \"Y\"), teal_slice(\"ADLB\", \"ONTRTFL\", selected = \"Y\") ) ) #> Initializing tm_t_abnormality_by_worst_grade #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_ancova.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: ANCOVA Summary — tm_t_ancova","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"module produces table summarize analysis variance, consistent TLG Catalog template AOVT01 available multiple endpoints selected.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_ancova.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"","code":"tm_t_ancova( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, arm_ref_comp = NULL, aval_var, cov_var, include_interact = FALSE, interact_var = NULL, interact_y = FALSE, avisit, paramcd, conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_ancova.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. cov_var (teal.transform::choices_selected()) object available choices preselected option covariates variables. include_interact (logical) whether interaction term included model. interact_var (character) name variable interactions arm. interaction needed, default option NULL. interact_y (character) selected item interact_var column used select specific ANCOVA results interact_var discrete. interaction needed, default option FALSE. avisit (teal.transform::choices_selected()) value analysis visit AVISIT interest. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_ancova.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_ancova.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"single endpoint selected, unadjusted adjusted comparison provided. modules expects analysis data following variables: AVISIT: variable used filter analysis visits. PARAMCD: variable used filter endpoints, filtering paramcd avisit, one observation per patient expected analysis meaningful.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_ancova.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"module generates following objects, can modified place using decorators: table (ElementaryTable - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_ancova.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_ancova.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: ANCOVA Summary — tm_t_ancova","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADQS <- tmc_ex_adqs }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADQS <- data[[\"ADQS\"]] arm_ref_comp <- list( ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ), ACTARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ) ) app <- init( data = data, modules = modules( tm_t_ancova( label = \"ANCOVA Table\", dataname = \"ADQS\", avisit = choices_selected( choices = value_choices(ADQS, \"AVISIT\"), selected = \"WEEK 1 DAY 8\" ), arm_var = choices_selected( choices = variable_choices(ADSL, c(\"ARM\", \"ACTARMCD\", \"ARMCD\")), selected = \"ARMCD\" ), arm_ref_comp = arm_ref_comp, aval_var = choices_selected( choices = variable_choices(ADQS, c(\"CHG\", \"AVAL\")), selected = \"CHG\" ), cov_var = choices_selected( choices = variable_choices(ADQS, c(\"BASE\", \"STRATA1\", \"SEX\")), selected = \"STRATA1\" ), paramcd = choices_selected( choices = value_choices(ADQS, \"PARAMCD\", \"PARAM\"), selected = \"FKSI-FWB\" ), interact_var = choices_selected( choices = variable_choices(ADQS, c(\"BASE\", \"STRATA1\", \"SEX\")), selected = \"STRATA1\" ) ) ) ) #> Initializing tm_t_ancova #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_binary_outcome.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Binary Outcome Table — tm_t_binary_outcome","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"module produces binary outcome response summary table, option match template response table RSPT01 available TLG Catalog .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_binary_outcome.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"","code":"tm_t_binary_outcome( label, dataname, parentname = ifelse(test = inherits(arm_var, \"data_extract_spec\"), yes = teal.transform::datanames_input(arm_var), no = \"ADSL\"), arm_var, arm_ref_comp = NULL, paramcd, strata_var, aval_var = teal.transform::choices_selected(choices = teal.transform::variable_choices(dataname, c(\"AVALC\", \"SEX\")), selected = \"AVALC\", fixed = FALSE), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), default_responses = c(\"CR\", \"PR\", \"Y\", \"Complete Response (CR)\", \"Partial Response (PR)\", \"M\"), rsp_table = FALSE, control = list(global = list(method = ifelse(rsp_table, \"clopper-pearson\", \"waldcc\"), conf_level = 0.95), unstrat = list(method_ci = ifelse(rsp_table, \"wald\", \"waldcc\"), method_test = \"schouten\", odds = TRUE), strat = list(method_ci = \"cmh\", method_test = \"cmh\")), add_total = FALSE, total_label = default_total_label(), na_level = default_na_str(), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_binary_outcome.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. strata_var (teal.transform::choices_selected()) names variables stratified analysis. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). default_responses (list character) defines default codes response variable module per value paramcd. passed vector transmitted paramcd values. passed list must named contain arrays, name corresponding single value paramcd. array may contain default response values named arrays rsp default selected response values levels default level choices. rsp_table (logical) whether initial set-module match RSPT01. Defaults FALSE. control (named list) named list containing 3 named lists follows: global: list settings overall analysis 2 named elements method conf_level. unstrat: list settings unstratified analysis 3 named elements method_ci method_test, odds. See tern::estimate_proportion_diff(), tern::test_proportion_diff(), tern::estimate_odds_ratio(), respectively, options details settings implemented analysis. strat: list settings stratified analysis elements method_ci method_test. See tern::estimate_proportion_diff() tern::test_proportion_diff(), respectively, options details settings implemented analysis. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_binary_outcome.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_binary_outcome.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"display order response categories inherits factor level order source data. Use base::factor() levels argument manipulate source data order include/exclude re-categorize response categories arrange display order. response categories \"Missing\", \"Evaluable (NE)\", \"Missing unevaluable\", 95% confidence interval calculated. Reference arms automatically combined multiple arms selected reference group.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_binary_outcome.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_binary_outcome.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_binary_outcome.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Binary Outcome Table — tm_t_binary_outcome","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADRS <- tmc_ex_adrs %>% mutate( AVALC = d_onco_rsp_label(AVALC) %>% with_label(\"Character Result/Finding\") ) %>% filter(PARAMCD != \"OVRINV\" | AVISIT == \"FOLLOW UP\") }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADRS <- data[[\"ADRS\"]] arm_ref_comp <- list( ARMCD = list(ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\")), ARM = list(ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\")) ) app <- init( data = data, modules = modules( tm_t_binary_outcome( label = \"Responders\", dataname = \"ADRS\", paramcd = choices_selected( choices = value_choices(ADRS, \"PARAMCD\", \"PARAM\"), selected = \"BESRSPI\" ), arm_var = choices_selected( choices = variable_choices(ADRS, c(\"ARM\", \"ARMCD\", \"ACTARMCD\")), selected = \"ARM\" ), arm_ref_comp = arm_ref_comp, strata_var = choices_selected( choices = variable_choices(ADRS, c(\"SEX\", \"BMRKR2\", \"RACE\")), selected = \"RACE\" ), default_responses = list( BESRSPI = list( rsp = c(\"Complete Response (CR)\", \"Partial Response (PR)\"), levels = c( \"Complete Response (CR)\", \"Partial Response (PR)\", \"Stable Disease (SD)\", \"Progressive Disease (PD)\" ) ), INVET = list( rsp = c(\"Stable Disease (SD)\", \"Not Evaluable (NE)\"), levels = c( \"Complete Response (CR)\", \"Not Evaluable (NE)\", \"Partial Response (PR)\", \"Progressive Disease (PD)\", \"Stable Disease (SD)\" ) ), OVRINV = list( rsp = c(\"Progressive Disease (PD)\", \"Stable Disease (SD)\"), levels = c(\"Progressive Disease (PD)\", \"Stable Disease (SD)\", \"Not Evaluable (NE)\") ) ) ) ) ) #> Initializing tm_t_binary_outcome #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_coxreg.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Cox Regression Model — tm_t_coxreg","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"module fits Cox univariable multi-variable models, consistent TLG Catalog templates Cox regression tables COXT01 COXT02, respectively. See TLG Catalog entries COXT01 COXT02 .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_coxreg.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"","code":"tm_t_coxreg( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, arm_ref_comp = NULL, paramcd, cov_var, strata_var, aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVAL\"), \"AVAL\", fixed = TRUE), cnsr_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"CNSR\"), \"CNSR\", fixed = TRUE), multivariate = TRUE, na_level = default_na_str(), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_coxreg.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. cov_var (teal.transform::choices_selected()) object available choices preselected option covariates variables. strata_var (teal.transform::choices_selected()) names variables stratified analysis. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. cnsr_var (teal.transform::choices_selected()) object available choices preselected option censoring variable. multivariate (logical) FALSE, univariable approach used instead multi-variable model. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_coxreg.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_coxreg.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"Cox Proportional Hazards (PH) model commonly used method estimate magnitude effect survival analysis. assumes proportional hazards: ratio hazards groups (e.g., two arms) constant time. ratio referred \"hazard ratio\" (HR) one commonly reported metrics describe effect size survival analysis. modules expects analysis data following variables: AVAL: time event CNSR: 1 record AVAL censored, 0 otherwise PARAMCD: variable used filter endpoint (e.g. OS). filtering PARAMCD one observation per patient expected arm variables stratification/covariate variables taken ADSL data.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_coxreg.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"likelihood ratio test supported models include strata - Wald test substituted cases. Multi-variable default choice backward compatibility.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_coxreg.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"module generates following objects, can modified place using decorators: table (TableTree created rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_coxreg.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"example-1 Open Shinylive example-2 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_coxreg.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Cox Regression Model — tm_t_coxreg","text":"","code":"## First example ## ============= ## The example below is based on the usual approach involving creation of ## a random CDISC dataset and then running the application. arm_ref_comp <- list( ACTARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ), ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ) ) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADTTE <- tmc_ex_adtte }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADTTE <- data[[\"ADTTE\"]] app <- init( data = data, modules = modules( tm_t_coxreg( label = \"Cox Reg.\", dataname = \"ADTTE\", arm_var = choices_selected(c(\"ARM\", \"ARMCD\", \"ACTARMCD\"), \"ARM\"), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( value_choices(ADTTE, \"PARAMCD\", \"PARAM\"), \"OS\" ), strata_var = choices_selected( c(\"COUNTRY\", \"STRATA1\", \"STRATA2\"), \"STRATA1\" ), cov_var = choices_selected( c(\"AGE\", \"BMRKR1\", \"BMRKR2\", \"REGION1\"), \"AGE\" ), multivariate = TRUE ) ) ) #> Initializing tm_t_coxreg #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) } ## Second example ## ============== ## This time, a synthetic pair of ADTTE/ADSL data is fabricated for Cox regression ## where ties and pval_method matter. library(dplyr) data <- teal_data() data <- within(data, { ADTTE <- data.frame( STUDYID = \"LUNG\", AVAL = c(4, 3, 1, 1, 2, 2, 3, 1, 2), CNSR = c(1, 1, 1, 0, 1, 1, 0, 0, 0), ARMCD = factor( c(0, 1, 1, 1, 1, 0, 0, 0, 0), labels = c(\"ARM A\", \"ARM B\") ), SEX = factor( c(0, 0, 0, 0, 1, 1, 1, 1, 1), labels = c(\"F\", \"M\") ), INST = factor(c(\"A\", \"A\", \"B\", \"B\", \"A\", \"B\", \"A\", \"B\", \"A\")), stringsAsFactors = FALSE ) ADTTE <- rbind(ADTTE, ADTTE, ADTTE, ADTTE) ADTTE <- as_tibble(ADTTE) set.seed(1) ADTTE$INST <- sample(ADTTE$INST) ADTTE$AGE <- sample(seq(5, 75, 5), size = nrow(ADTTE), replace = TRUE) ADTTE$USUBJID <- paste(\"sub\", 1:nrow(ADTTE), ADTTE$INST, sep = \"-\") ADTTE$PARAM <- ADTTE$PARAMCD <- \"OS\" ADSL <- subset( ADTTE, select = c(\"USUBJID\", \"STUDYID\", \"ARMCD\", \"SEX\", \"INST\", \"AGE\") ) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADTTE <- data[[\"ADTTE\"]] ## `teal` application ## ---------------- ## Note that the R code exported by `Show R Code` does not include the data ## pre-processing. You will need to create the dataset as above before ## running the exported R code. arm_ref_comp <- list(ARMCD = list(ref = \"ARM A\", comp = c(\"ARM B\"))) app <- init( data = data, modules = modules( tm_t_coxreg( label = \"Cox Reg.\", dataname = \"ADTTE\", arm_var = choices_selected(c(\"ARMCD\"), \"ARMCD\"), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( value_choices(ADTTE, \"PARAMCD\", \"PARAM\"), \"OS\" ), strata_var = choices_selected(c(\"INST\"), NULL), cov_var = choices_selected(c(\"SEX\", \"AGE\"), \"SEX\"), multivariate = TRUE ) ) ) #> Initializing tm_t_coxreg #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Events by Term — tm_t_events","title":"teal Module: Events by Term — tm_t_events","text":"module produces table events term.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Events by Term — tm_t_events","text":"","code":"tm_t_events( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, hlt, llt, add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), event_type = \"event\", sort_criteria = c(\"freq_desc\", \"alpha\"), sort_freq_col = total_label, prune_freq = 0, prune_diff = 0, drop_arm_levels = TRUE, incl_overall_sum = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Events by Term — tm_t_events","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. hlt (teal.transform::choices_selected()) name variable high level term events. llt (teal.transform::choices_selected()) name variable low level term events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). event_type (character) type event summarized (e.g. adverse event, treatment). Default \"event\". sort_criteria (character) sort final table. Default option freq_desc sorts column sort_freq_col decreasing number patients event. Alternative option alpha sorts events alphabetically. sort_freq_col (character) column sort frequency sort_criteria set freq_desc. prune_freq (number) threshold use trimming table using event incidence rate column. prune_diff (number) threshold use trimming table using criteria difference rates two columns. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. incl_overall_sum (flag) whether two rows summarize overall number adverse events included top table. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Events by Term — tm_t_events","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Events by Term — tm_t_events","text":"module generates following objects, can modified place using decorators: table (TableTree created rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Events by Term — tm_t_events","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Events by Term — tm_t_events","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADAE <- tmc_ex_adae }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADAE <- data[[\"ADAE\"]] app <- init( data = data, modules = modules( tm_t_events( label = \"Adverse Event Table\", dataname = \"ADAE\", arm_var = choices_selected(c(\"ARM\", \"ARMCD\"), \"ARM\"), llt = choices_selected( choices = variable_choices(ADAE, c(\"AETERM\", \"AEDECOD\")), selected = c(\"AEDECOD\") ), hlt = choices_selected( choices = variable_choices(ADAE, c(\"AEBODSYS\", \"AESOC\")), selected = \"AEBODSYS\" ), add_total = TRUE, event_type = \"adverse event\" ) ) ) #> Initializing tm_t_events #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_by_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Events by Grade — tm_t_events_by_grade","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"module produces table summarize events grade.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_by_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"","code":"tm_t_events_by_grade( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, hlt, llt, grade, grading_groups = list(`Any Grade (%)` = c(\"1\", \"2\", \"3\", \"4\", \"5\"), `Grade 1-2 (%)` = c(\"1\", \"2\"), `Grade 3-4 (%)` = c(\"3\", \"4\"), `Grade 5 (%)` = \"5\"), col_by_grade = FALSE, prune_freq = 0, prune_diff = 0, add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_by_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. hlt (teal.transform::choices_selected()) name variable high level term events. llt (teal.transform::choices_selected()) name variable low level term events. grade (character) name severity level variable. grading_groups (list) named list grading groups used col_by_grade = TRUE. col_by_grade (logical) whether display grading groups nested columns. prune_freq (number) threshold use trimming table using event incidence rate column. prune_diff (number) threshold use trimming table using criteria difference rates two columns. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_by_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_by_grade.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"module generates following objects, can modified place using decorators: table (TableTree created rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_by_grade.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_by_grade.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Events by Grade — tm_t_events_by_grade","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl .lbls_adae <- col_labels(tmc_ex_adae) ADAE <- tmc_ex_adae %>% mutate_if(is.character, as.factor) #' be certain of having factors col_labels(ADAE) <- .lbls_adae }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADAE <- data[[\"ADAE\"]] app <- init( data = data, modules = modules( tm_t_events_by_grade( label = \"Adverse Events by Grade Table\", dataname = \"ADAE\", arm_var = choices_selected(c(\"ARM\", \"ARMCD\"), \"ARM\"), llt = choices_selected( choices = variable_choices(ADAE, c(\"AETERM\", \"AEDECOD\")), selected = c(\"AEDECOD\") ), hlt = choices_selected( choices = variable_choices(ADAE, c(\"AEBODSYS\", \"AESOC\")), selected = \"AEBODSYS\" ), grade = choices_selected( choices = variable_choices(ADAE, c(\"AETOXGR\", \"AESEV\")), selected = \"AETOXGR\" ) ) ) ) #> Initializing tm_t_events_by_grade #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_patyear.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"module produces table event rates adjusted patient-years.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_patyear.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"","code":"tm_t_events_patyear( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, events_var, paramcd, aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVAL\"), \"AVAL\", fixed = TRUE), avalu_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALU\"), \"AVALU\", fixed = TRUE), add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_patyear.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. events_var (teal.transform::choices_selected()) object available choices preselected option variable event counts. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. avalu_var (teal.transform::choices_selected()) object available choices preselected option analysis unit variable. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_patyear.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_patyear.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"module generates following objects, can modified place using decorators: table (TableTree created rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_patyear.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"example-1 Open Shinylive example-2 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_patyear.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Event Rates Adjusted for Patient-Years — tm_t_events_patyear","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADAETTE <- tmc_ex_adaette %>% filter(PARAMCD %in% c(\"AETTE1\", \"AETTE2\", \"AETTE3\")) %>% mutate(is_event = CNSR == 0) %>% mutate(n_events = as.integer(is_event)) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADAETTE <- data[[\"ADAETTE\"]] # 1. Basic Example app <- init( data = data, modules = modules( tm_t_events_patyear( label = \"AE Rate Adjusted for Patient-Years At Risk Table\", dataname = \"ADAETTE\", arm_var = choices_selected( choices = variable_choices(ADSL, c(\"ARM\", \"ARMCD\")), selected = \"ARMCD\" ), add_total = TRUE, events_var = choices_selected( choices = variable_choices(ADAETTE, \"n_events\"), selected = \"n_events\", fixed = TRUE ), paramcd = choices_selected( choices = value_choices(ADAETTE, \"PARAMCD\", \"PARAM\"), selected = \"AETTE1\" ) ) ) ) #> Initializing tm_t_events_patyear #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) } # 2. Example with table split on 2 arm_var variables app <- init( data = data, modules = modules( tm_t_events_patyear( label = \"AE Rate Adjusted for Patient-Years At Risk Table\", dataname = \"ADAETTE\", arm_var = choices_selected( choices = variable_choices(ADSL, c(\"ARM\", \"ARMCD\", \"SEX\")), selected = c(\"ARM\", \"SEX\") ), add_total = TRUE, events_var = choices_selected( choices = variable_choices(ADAETTE, \"n_events\"), selected = \"n_events\", fixed = TRUE ), paramcd = choices_selected( choices = value_choices(ADAETTE, \"PARAMCD\", \"PARAM\"), selected = \"AETTE1\" ) ) ) ) #> Initializing tm_t_events_patyear #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_summary.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Adverse Events Summary — tm_t_events_summary","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"module produces adverse events summary table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_summary.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"","code":"tm_t_events_summary( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, flag_var_anl = NULL, flag_var_aesi = NULL, dthfl_var = teal.transform::choices_selected(teal.transform::variable_choices(parentname, \"DTHFL\"), \"DTHFL\", fixed = TRUE), dcsreas_var = teal.transform::choices_selected(teal.transform::variable_choices(parentname, \"DCSREAS\"), \"DCSREAS\", fixed = TRUE), llt = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AEDECOD\"), \"AEDECOD\", fixed = TRUE), aeseq_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AESEQ\"), \"AESEQ\", fixed = TRUE), add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), count_dth = TRUE, count_wd = TRUE, count_subj = TRUE, count_pt = TRUE, count_events = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_summary.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. flag_var_anl (teal.transform::choices_selected() NULL) vector names flag variables dataset used count adverse event sub-groups (e.g. Serious events, Related events, etc.). Variable labels used table row names exist. flag_var_aesi (teal.transform::choices_selected() NULL) vector names flag variables dataset used count adverse event special interest groups. flag variables must type logical. Variable labels used table row names exist. dthfl_var (teal.transform::choices_selected()) object available choices preselected option variable names can used death flag variable. Records `\"Y\"“ summarized table row \"Total number deaths\". dcsreas_var (teal.transform::choices_selected()) object available choices preselected option variable names can used study discontinuation reason variable. Records \"ADVERSE EVENTS\" summarized table row \"Total number patients withdrawn study due AE\". llt (teal.transform::choices_selected()) name variable low level term events. aeseq_var (teal.transform::choices_selected()) variable adverse events sequence number dataset. Used counting total number events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). count_dth (logical) whether show count total deaths (based dthfl_var). Defaults TRUE. count_wd (logical) whether show count patients withdrawn study due adverse event (based dcsreas_var). Defaults TRUE. count_subj (logical) whether show count unique subjects (based USUBJID). applies event flag variables provided. count_pt (logical) whether show count unique preferred terms (based llt). applies event flag variables provided. count_events (logical) whether show count events (based aeseq_var). applies event flag variables provided. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_summary.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_summary.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"module generates following objects, can modified place using decorators: table (TableTree created rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_summary.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_events_summary.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Adverse Events Summary — tm_t_events_summary","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl %>% mutate( DTHFL = case_when( !is.na(DTHDT) ~ \"Y\", TRUE ~ \"\" ) %>% with_label(\"Subject Death Flag\") ) ADAE <- tmc_ex_adae .add_event_flags <- function(dat) { dat <- dat %>% mutate( TMPFL_SER = AESER == \"Y\", TMPFL_REL = AEREL == \"Y\", TMPFL_GR5 = AETOXGR == \"5\", TMP_SMQ01 = !is.na(SMQ01NAM), TMP_SMQ02 = !is.na(SMQ02NAM), TMP_CQ01 = !is.na(CQ01NAM) ) column_labels <- list( TMPFL_SER = \"Serious AE\", TMPFL_REL = \"Related AE\", TMPFL_GR5 = \"Grade 5 AE\", TMP_SMQ01 = aesi_label(dat[[\"SMQ01NAM\"]], dat[[\"SMQ01SC\"]]), TMP_SMQ02 = aesi_label(\"Y.9.9.9.9/Z.9.9.9.9 AESI\"), TMP_CQ01 = aesi_label(dat[[\"CQ01NAM\"]]) ) col_labels(dat)[names(column_labels)] <- as.character(column_labels) dat } #' Generating user-defined event flags. ADAE <- ADAE %>% .add_event_flags() .ae_anl_vars <- names(ADAE)[startsWith(names(ADAE), \"TMPFL_\")] .aesi_vars <- names(ADAE)[startsWith(names(ADAE), \"TMP_\")] }) join_keys(data) <- default_cdisc_join_keys[names(data)] app <- init( data = data, modules = modules( tm_t_events_summary( label = \"Adverse Events Summary\", dataname = \"ADAE\", arm_var = choices_selected( choices = variable_choices(\"ADSL\", c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), flag_var_anl = choices_selected( choices = variable_choices(\"ADAE\", data[[\".ae_anl_vars\"]]), selected = data[[\".ae_anl_vars\"]][1], keep_order = TRUE, fixed = FALSE ), flag_var_aesi = choices_selected( choices = variable_choices(\"ADAE\", data[[\".aesi_vars\"]]), selected = data[[\".aesi_vars\"]][1], keep_order = TRUE, fixed = FALSE ), add_total = TRUE ) ) ) #> Initializing tm_t_events_summary #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_exposure.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"module produces exposure table risk management plan.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_exposure.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"","code":"tm_t_exposure( label, dataname, parentname = ifelse(inherits(col_by_var, \"data_extract_spec\"), teal.transform::datanames_input(col_by_var), \"ADSL\"), row_by_var, col_by_var, paramcd = teal.transform::choices_selected(choices = teal.transform::value_choices(dataname, \"PARAMCD\", \"PARAM\"), selected = \"TDURD\"), paramcd_label = \"PARAM\", id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"USUBJID\"), selected = \"USUBJID\", fixed = TRUE), parcat, aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"AVAL\"), selected = \"AVAL\", fixed = TRUE), avalu_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"AVALU\"), selected = \"AVALU\", fixed = TRUE), add_total, total_label = default_total_label(), add_total_row = TRUE, total_row_label = \"Total number of patients and patient time*\", na_level = default_na_str(), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_exposure.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. row_by_var (teal.transform::choices_selected()) object available choices preselected option variable names can used split rows. col_by_var (teal.transform::choices_selected()) object available choices preselected option variable names can used split columns. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. paramcd_label (character) column dataset value used label argument paramcd. id_var (teal.transform::choices_selected()) object specifying variable name subject id. parcat (teal.transform::choices_selected()) object available choices preselected option parameter category values. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. avalu_var (teal.transform::choices_selected()) object available choices preselected option analysis unit variable. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). add_total_row (flag) whether \"total\" level added others includes levels constitute split. custom label can set level via total_row_label argument. total_row_label (character) string display total row label row enabled (see add_total_row). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_exposure.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_exposure.html","id":"decorating-modules","dir":"Reference","previous_headings":"","what":"Decorating Modules","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"module generates following objects, can modified place using decorators: table (TableTree created rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_exposure.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_exposure.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Exposure Table for Risk management plan — tm_t_exposure","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADEX <- tmc_ex_adex set.seed(1, kind = \"Mersenne-Twister\") .labels <- col_labels(ADEX, fill = FALSE) ADEX <- ADEX %>% distinct(USUBJID, .keep_all = TRUE) %>% mutate( PARAMCD = \"TDURD\", PARAM = \"Overall duration (days)\", AVAL = sample(x = seq(1, 200), size = n(), replace = TRUE), AVALU = \"Days\" ) %>% bind_rows(ADEX) col_labels(ADEX) <- .labels }) join_keys(data) <- default_cdisc_join_keys[names(data)] app <- init( data = data, modules = modules( tm_t_exposure( label = \"Duration of Exposure Table\", dataname = \"ADEX\", paramcd = choices_selected( choices = value_choices(data[[\"ADEX\"]], \"PARAMCD\", \"PARAM\"), selected = \"TDURD\" ), col_by_var = choices_selected( choices = variable_choices(data[[\"ADEX\"]], subset = c(\"SEX\", \"ARM\")), selected = \"SEX\" ), row_by_var = choices_selected( choices = variable_choices(data[[\"ADEX\"]], subset = c(\"RACE\", \"REGION1\", \"STRATA1\", \"SEX\")), selected = \"RACE\" ), parcat = choices_selected( choices = value_choices(data[[\"ADEX\"]], \"PARCAT2\"), selected = \"Drug A\" ), add_total = FALSE ) ), filter = teal_slices(teal_slice(\"ADSL\", \"SAFFL\", selected = \"Y\")) ) #> Initializing tm_t_exposure #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_logistic.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Logistic Regression — tm_t_logistic","title":"teal Module: Logistic Regression — tm_t_logistic","text":"module produces multi-variable logistic regression table consistent TLG Catalog template LGRT02 available .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_logistic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Logistic Regression — tm_t_logistic","text":"","code":"tm_t_logistic( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var = NULL, arm_ref_comp = NULL, paramcd, cov_var = NULL, avalc_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALC\"), \"AVALC\", fixed = TRUE), conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_logistic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Logistic Regression — tm_t_logistic","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected() NULL) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. NULL, arm/treatment variable included logistic model. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. cov_var (teal.transform::choices_selected()) object available choices preselected option covariates variables. avalc_var (teal.transform::choices_selected()) object available choices preselected option analysis variable (categorical). conf_level (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_logistic.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Logistic Regression — tm_t_logistic","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_logistic.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Logistic Regression — tm_t_logistic","text":"module generates following objects, can modified place using decorators: table (ElementaryTable - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_logistic.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Logistic Regression — tm_t_logistic","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_logistic.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Logistic Regression — tm_t_logistic","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADRS <- tmc_ex_adrs %>% filter(PARAMCD %in% c(\"BESRSPI\", \"INVET\")) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADRS <- data[[\"ADRS\"]] arm_ref_comp <- list( ACTARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ), ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ) ) app <- init( data = data, modules = modules( tm_t_logistic( label = \"Logistic Regression\", dataname = \"ADRS\", arm_var = choices_selected( choices = variable_choices(ADRS, c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( choices = value_choices(ADRS, \"PARAMCD\", \"PARAM\"), selected = \"BESRSPI\" ), cov_var = choices_selected( choices = c(\"SEX\", \"AGE\", \"BMRKR1\", \"BMRKR2\"), selected = \"SEX\" ) ) ) ) #> Initializing tm_t_logistic #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_mult_events.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Multiple Events by Term — tm_t_mult_events","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"module produces table multiple events term.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_mult_events.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"","code":"tm_t_mult_events( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, seq_var, hlt, llt, add_total = TRUE, total_label = default_total_label(), na_level = default_na_str(), event_type = \"event\", drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_mult_events.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. seq_var (teal.transform::choices_selected()) object available choices preselected option variable names can used analysis sequence number variable. Used counting unique number events. hlt (teal.transform::choices_selected()) name variable high level term events. llt (teal.transform::choices_selected()) name variable low level term events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). event_type (character) type event summarized (e.g. adverse event, treatment). Default \"event\". drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_mult_events.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_mult_events.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_mult_events.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_mult_events.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Multiple Events by Term — tm_t_mult_events","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADCM <- tmc_ex_adcm }) join_keys(data) <- default_cdisc_join_keys[names(data)] adcm_keys <- c(\"STUDYID\", \"USUBJID\", \"ASTDTM\", \"CMSEQ\", \"ATC1\", \"ATC2\", \"ATC3\", \"ATC4\") join_keys(data)[\"ADCM\", \"ADCM\"] <- adcm_keys ADSL <- data[[\"ADSL\"]] ADCM <- data[[\"ADCM\"]] app <- init( data = data, modules = modules( tm_t_mult_events( label = \"Concomitant Medications by Medication Class and Preferred Name\", dataname = \"ADCM\", arm_var = choices_selected(c(\"ARM\", \"ARMCD\"), \"ARM\"), seq_var = choices_selected(\"CMSEQ\", selected = \"CMSEQ\", fixed = TRUE), hlt = choices_selected( choices = variable_choices(ADCM, c(\"ATC1\", \"ATC2\", \"ATC3\", \"ATC4\")), selected = c(\"ATC1\", \"ATC2\", \"ATC3\", \"ATC4\") ), llt = choices_selected( choices = variable_choices(ADCM, c(\"CMDECOD\")), selected = c(\"CMDECOD\") ), add_total = TRUE, event_type = \"treatment\" ) ) ) #> Initializing tm_t_mult_events #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_basic_info.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"module produces patient profile basic info report using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_basic_info.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"","code":"tm_t_pp_basic_info( label, dataname = \"ADSL\", patient_col = \"USUBJID\", vars = NULL, pre_output = NULL, post_output = NULL, decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_basic_info.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. patient_col (character) name patient ID variable. vars (teal.transform::choices_selected()) object available choices preselected option variables dataname show table. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_basic_info.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_basic_info.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"module generates following objects, can modified place using decorators: table (listing_df - output rlistings::as_listing) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_basic_info.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_basic_info.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Basic Info — tm_t_pp_basic_info","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] app <- init( data = data, modules = modules( tm_t_pp_basic_info( label = \"Basic Info\", dataname = \"ADSL\", patient_col = \"USUBJID\", vars = choices_selected( choices = variable_choices(ADSL), selected = c(\"ARM\", \"AGE\", \"SEX\", \"COUNTRY\", \"RACE\", \"EOSSTT\") ) ) ) ) #> Initializing tm_t_pp_basic_info #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_laboratory.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"module produces patient profile laboratory table using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_laboratory.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"","code":"tm_t_pp_laboratory( label, dataname = \"ADLB\", parentname = \"ADSL\", patient_col = \"USUBJID\", timepoints = NULL, aval = lifecycle::deprecated(), aval_var = NULL, avalu = lifecycle::deprecated(), avalu_var = NULL, param = NULL, paramcd = NULL, anrind = NULL, pre_output = NULL, post_output = NULL, decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_laboratory.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. timepoints (teal.transform::choices_selected()) object available choices preselected option time variable dataname. aval Please use aval_var argument instead. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. avalu Please use avalu_var argument instead. avalu_var (teal.transform::choices_selected()) object available choices preselected option analysis unit variable. param (teal.transform::choices_selected()) object available choices preselected option PARAM variable dataname. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. anrind (teal.transform::choices_selected()) object available choices preselected option ANRIND variable dataname. Variable following 3 levels: \"HIGH\", \"LOW\", \"NORMAL\". pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_laboratory.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_laboratory.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"module generates following objects, can modified place using decorators: table (listing_df - output rlistings::as_listing) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_laboratory.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_laboratory.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Laboratory Table — tm_t_pp_laboratory","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_t_pp_laboratory( label = \"Vitals\", dataname = \"ADLB\", patient_col = \"USUBJID\", paramcd = choices_selected( choices = variable_choices(ADLB, \"PARAMCD\"), selected = \"PARAMCD\" ), param = choices_selected( choices = variable_choices(ADLB, \"PARAM\"), selected = \"PARAM\" ), timepoints = choices_selected( choices = variable_choices(ADLB, \"ADY\"), selected = \"ADY\" ), anrind = choices_selected( choices = variable_choices(ADLB, \"ANRIND\"), selected = \"ANRIND\" ), aval_var = choices_selected( choices = variable_choices(ADLB, \"AVAL\"), selected = \"AVAL\" ), avalu_var = choices_selected( choices = variable_choices(ADLB, \"AVALU\"), selected = \"AVALU\" ) ) ) ) #> Initializing tm_t_pp_laboratory #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_medical_history.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"module produces patient profile medical history report using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_medical_history.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"","code":"tm_t_pp_medical_history( label, dataname = \"ADMH\", parentname = \"ADSL\", patient_col = \"USUBJID\", mhterm = NULL, mhbodsys = NULL, mhdistat = NULL, pre_output = NULL, post_output = NULL, decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_medical_history.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. mhterm (teal.transform::choices_selected()) object available choices preselected option MHTERM variable dataname. mhbodsys (teal.transform::choices_selected()) object available choices preselected option MHBODSYS variable dataname. mhdistat (teal.transform::choices_selected()) object available choices preselected option MHDISTAT variable dataname. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_medical_history.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_medical_history.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_medical_history.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_medical_history.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Medical History — tm_t_pp_medical_history","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADMH <- tmc_ex_admh }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADMH <- data[[\"ADMH\"]] app <- init( data = data, modules = modules( tm_t_pp_medical_history( label = \"Medical History\", dataname = \"ADMH\", parentname = \"ADSL\", patient_col = \"USUBJID\", mhterm = choices_selected( choices = variable_choices(ADMH, c(\"MHTERM\")), selected = \"MHTERM\" ), mhbodsys = choices_selected( choices = variable_choices(ADMH, \"MHBODSYS\"), selected = \"MHBODSYS\" ), mhdistat = choices_selected( choices = variable_choices(ADMH, \"MHDISTAT\"), selected = \"MHDISTAT\" ) ) ) ) #> Initializing tm_t_pp_medical_history #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_prior_medication.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"module produces patient profile prior medication report using ADaM datasets.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_prior_medication.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"","code":"tm_t_pp_prior_medication( label, dataname = \"ADCM\", parentname = \"ADSL\", patient_col = \"USUBJID\", atirel = NULL, cmdecod = NULL, cmindc = NULL, cmstdy = NULL, pre_output = NULL, post_output = NULL, decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_prior_medication.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. patient_col (character) name patient ID variable. atirel (teal.transform::choices_selected()) object available choices preselected option ATIREL variable dataname. cmdecod (teal.transform::choices_selected()) object available choices preselected option CMDECOD variable dataname. cmindc (teal.transform::choices_selected()) object available choices preselected option CMINDC variable dataname. cmstdy (teal.transform::choices_selected()) object available choices preselected option CMSTDY variable dataname. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_prior_medication.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_prior_medication.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"module generates following objects, can modified place using decorators: table (listing_df - output rlistings::as_listing) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_prior_medication.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_pp_prior_medication.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Patient Profile Prior Medication — tm_t_pp_prior_medication","text":"","code":"library(dplyr) data <- teal_data() data <- within(data, { ADCM <- tmc_ex_adcm ADSL <- tmc_ex_adsl %>% filter(USUBJID %in% ADCM$USUBJID) ADCM$CMASTDTM <- ADCM$ASTDTM ADCM$CMAENDTM <- ADCM$AENDTM }) join_keys(data) <- default_cdisc_join_keys[names(data)] adcm_keys <- c(\"STUDYID\", \"USUBJID\", \"ASTDTM\", \"CMSEQ\", \"ATC1\", \"ATC2\", \"ATC3\", \"ATC4\") join_keys(data)[\"ADCM\", \"ADCM\"] <- adcm_keys ADSL <- data[[\"ADSL\"]] ADCM <- data[[\"ADCM\"]] app <- init( data = data, modules = modules( tm_t_pp_prior_medication( label = \"Prior Medication\", dataname = \"ADCM\", parentname = \"ADSL\", patient_col = \"USUBJID\", atirel = choices_selected( choices = variable_choices(ADCM, \"ATIREL\"), selected = \"ATIREL\" ), cmdecod = choices_selected( choices = variable_choices(ADCM, \"CMDECOD\"), selected = \"CMDECOD\" ), cmindc = choices_selected( choices = variable_choices(ADCM, \"CMINDC\"), selected = \"CMINDC\" ), cmstdy = choices_selected( choices = variable_choices(ADCM, \"ASTDY\"), selected = \"ASTDY\" ) ) ) ) #> Initializing tm_t_pp_prior_medication #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Shift by Arm — tm_t_shift_by_arm","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"module produces summary table analysis indicator levels arm.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"","code":"tm_t_shift_by_arm( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, paramcd, visit_var, aval_var, base_var = lifecycle::deprecated(), baseline_var, treatment_flag_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"ONTRTFL\"), selected = \"ONTRTFL\"), treatment_flag = teal.transform::choices_selected(\"Y\"), useNA = c(\"ifany\", \"no\"), na_level = default_na_str(), add_total = FALSE, total_label = default_total_label(), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. visit_var (teal.transform::choices_selected()) object available choices preselected option variable names can used visit variable. Must factor dataname. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. base_var Please use baseline_var argument instead. baseline_var (teal.transform::choices_selected()) object available choices preselected option variable values can used baseline_var. treatment_flag_var (teal.transform::choices_selected()) treatment flag variable. treatment_flag (teal.transform::choices_selected()) value indicating treatment records treatment_flag_var. useNA (character) whether missing data (NA) displayed level. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). add_total (logical) whether include row total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Shift by Arm — tm_t_shift_by_arm","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADEG <- tmc_ex_adeg }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADEG <- data[[\"ADEG\"]] app <- init( data = data, modules = modules( tm_t_shift_by_arm( label = \"Shift by Arm Table\", dataname = \"ADEG\", arm_var = choices_selected( variable_choices(ADSL, subset = c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), paramcd = choices_selected( value_choices(ADEG, \"PARAMCD\"), selected = \"HR\" ), visit_var = choices_selected( value_choices(ADEG, \"AVISIT\"), selected = \"POST-BASELINE MINIMUM\" ), aval_var = choices_selected( variable_choices(ADEG, subset = \"ANRIND\"), selected = \"ANRIND\", fixed = TRUE ), baseline_var = choices_selected( variable_choices(ADEG, subset = \"BNRIND\"), selected = \"BNRIND\", fixed = TRUE ), useNA = \"ifany\" ) ) ) #> Initializing tm_t_shift_by_arm #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm_by_worst.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"module produces summary table worst analysis indicator variable level per subject arm.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm_by_worst.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"","code":"tm_t_shift_by_arm_by_worst( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, paramcd, aval_var, base_var = lifecycle::deprecated(), baseline_var, worst_flag_var, worst_flag, treatment_flag_var = teal.transform::choices_selected(choices = teal.transform::variable_choices(dataname, subset = \"ONTRTFL\"), selected = \"ONTRTFL\"), treatment_flag = teal.transform::choices_selected(\"Y\"), useNA = c(\"ifany\", \"no\"), na_level = default_na_str(), add_total = FALSE, total_label = default_total_label(), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm_by_worst.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. base_var Please use baseline_var argument instead. baseline_var (teal.transform::choices_selected()) object available choices preselected option variable values can used baseline_var. worst_flag_var (teal.transform::choices_selected()) object available choices preselected option variable names can used worst flag variable. worst_flag (character) value indicating worst analysis indicator level. treatment_flag_var (teal.transform::choices_selected()) treatment flag variable. treatment_flag (teal.transform::choices_selected()) value indicating treatment records treatment_flag_var. useNA (character) whether missing data (NA) displayed level. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). add_total (logical) whether include row total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm_by_worst.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm_by_worst.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm_by_worst.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_arm_by_worst.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Shift by Arm by Worst Analysis Indicator Level — tm_t_shift_by_arm_by_worst","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADEG <- tmc_ex_adeg }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADEG <- data[[\"ADEG\"]] app <- init( data = data, modules = modules( tm_t_shift_by_arm_by_worst( label = \"Shift by Arm Table\", dataname = \"ADEG\", arm_var = choices_selected( variable_choices(ADSL, subset = c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), paramcd = choices_selected( value_choices(ADEG, \"PARAMCD\"), selected = \"ECGINTP\" ), worst_flag_var = choices_selected( variable_choices(ADEG, c(\"WORS02FL\", \"WORS01FL\")), selected = \"WORS02FL\" ), worst_flag = choices_selected( value_choices(ADEG, \"WORS02FL\"), selected = \"Y\", fixed = TRUE ), aval_var = choices_selected( variable_choices(ADEG, c(\"AVALC\", \"ANRIND\")), selected = \"AVALC\" ), baseline_var = choices_selected( variable_choices(ADEG, c(\"BASEC\", \"BNRIND\")), selected = \"BASEC\" ), useNA = \"ifany\" ) ) ) #> Initializing tm_t_shift_by_arm_by_worst #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_grade.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Grade Summary Table — tm_t_shift_by_grade","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"module produces summary table worst grades per subject visit parameter.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_grade.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"","code":"tm_t_shift_by_grade( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, visit_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"AVISIT\"), selected = \"AVISIT\", fixed = TRUE), paramcd, worst_flag_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = c(\"WGRLOVFL\", \"WGRLOFL\", \"WGRHIVFL\", \"WGRHIFL\")), selected = \"WGRLOVFL\"), worst_flag_indicator = teal.transform::choices_selected(teal.transform::value_choices(dataname, \"WGRLOVFL\"), selected = \"Y\", fixed = TRUE), anl_toxgrade_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = c(\"ATOXGR\")), selected = c(\"ATOXGR\"), fixed = TRUE), base_toxgrade_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = c(\"BTOXGR\")), selected = c(\"BTOXGR\"), fixed = TRUE), id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"USUBJID\"), selected = \"USUBJID\", fixed = TRUE), add_total = FALSE, total_label = default_total_label(), drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, na_level = default_na_str(), code_missing_baseline = FALSE, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_grade.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. visit_var (teal.transform::choices_selected()) object available choices preselected option variable names can used visit variable. Must factor dataname. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. worst_flag_var (teal.transform::choices_selected()) object available choices preselected option variable names can used worst flag variable. worst_flag_indicator (teal.transform::choices_selected()) value indicating worst grade. anl_toxgrade_var (teal.transform::choices_selected()) variable analysis toxicity grade. base_toxgrade_var (teal.transform::choices_selected()) variable baseline toxicity grade. id_var (teal.transform::choices_selected()) object specifying variable name subject id. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). code_missing_baseline (logical) whether missing baseline grades counted grade 0. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_grade.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_grade.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_grade.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_shift_by_grade.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Grade Summary Table — tm_t_shift_by_grade","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_t_shift_by_grade( label = \"Grade Laboratory Abnormality Table\", dataname = \"ADLB\", arm_var = choices_selected( choices = variable_choices(ADSL, subset = c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), paramcd = choices_selected( choices = value_choices(ADLB, \"PARAMCD\", \"PARAM\"), selected = \"ALT\" ), worst_flag_var = choices_selected( choices = variable_choices(ADLB, subset = c(\"WGRLOVFL\", \"WGRLOFL\", \"WGRHIVFL\", \"WGRHIFL\")), selected = c(\"WGRLOVFL\") ), worst_flag_indicator = choices_selected( value_choices(ADLB, \"WGRLOVFL\"), selected = \"Y\", fixed = TRUE ), anl_toxgrade_var = choices_selected( choices = variable_choices(ADLB, subset = c(\"ATOXGR\")), selected = c(\"ATOXGR\"), fixed = TRUE ), base_toxgrade_var = choices_selected( choices = variable_choices(ADLB, subset = c(\"BTOXGR\")), selected = c(\"BTOXGR\"), fixed = TRUE ), add_total = FALSE ) ), filter = teal_slices(teal_slice(\"ADSL\", \"SAFFL\", selected = \"Y\")) ) #> Initializing tm_t_shift_by_grade #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_smq.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"module produces adverse events table Standardized MedDRA Query.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_smq.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"","code":"tm_t_smq( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"USUBJID\"), selected = \"USUBJID\", fixed = TRUE), llt, add_total = TRUE, total_label = default_total_label(), sort_criteria = c(\"freq_desc\", \"alpha\"), drop_arm_levels = TRUE, na_level = default_na_str(), smq_varlabel = \"Standardized MedDRA Query\", baskets, scopes, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_smq.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. id_var (teal.transform::choices_selected()) object specifying variable name subject id. llt (teal.transform::choices_selected()) name variable low level term events. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). sort_criteria (character) sort final table. Default option freq_desc sorts column sort_freq_col decreasing number patients event. Alternative option alpha sorts events alphabetically. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). smq_varlabel (character) label use new column SMQ created tern::h_stack_by_baskets(). baskets (teal.transform::choices_selected()) object available choices preselected options standardized/customized queries. scopes (teal.transform::choices_selected()) object available choices scopes standardized queries. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_smq.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_smq.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_smq.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_smq.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Adverse Events Table by Standardized MedDRA Query — tm_t_smq","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADAE <- tmc_ex_adae .names_baskets <- grep(\"^(SMQ|CQ).*NAM$\", names(ADAE), value = TRUE) .names_scopes <- grep(\"^SMQ.*SC$\", names(ADAE), value = TRUE) .cs_baskets <- choices_selected( choices = variable_choices(ADAE, subset = .names_baskets), selected = .names_baskets ) .cs_scopes <- choices_selected( choices = variable_choices(ADAE, subset = .names_scopes), selected = .names_scopes, fixed = TRUE ) }) join_keys(data) <- default_cdisc_join_keys[names(data)] app <- init( data = data, modules = modules( tm_t_smq( label = \"Adverse Events by SMQ Table\", dataname = \"ADAE\", arm_var = choices_selected( choices = variable_choices(data[[\"ADSL\"]], subset = c(\"ARM\", \"SEX\")), selected = \"ARM\" ), add_total = FALSE, baskets = data[[\".cs_baskets\"]], scopes = data[[\".cs_scopes\"]], llt = choices_selected( choices = variable_choices(data[[\"ADAE\"]], subset = c(\"AEDECOD\")), selected = \"AEDECOD\" ) ) ) ) #> Initializing tm_t_smq #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Summary of Variables — tm_t_summary","title":"teal Module: Summary of Variables — tm_t_summary","text":"module produces table summarize variables.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Summary of Variables — tm_t_summary","text":"","code":"tm_t_summary( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, summarize_vars, add_total = TRUE, total_label = default_total_label(), show_arm_var_labels = TRUE, useNA = c(\"ifany\", \"no\"), na_level = default_na_str(), numeric_stats = c(\"n\", \"mean_sd\", \"mean_ci\", \"median\", \"median_ci\", \"quantiles\", \"range\", \"geom_mean\"), denominator = c(\"N\", \"n\", \"omit\"), drop_arm_levels = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Summary of Variables — tm_t_summary","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. summarize_vars (teal.transform::choices_selected()) names variables summarized. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). show_arm_var_labels (flag) whether arm variable label(s) displayed. Defaults TRUE. useNA (character) whether missing data (NA) displayed level. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). numeric_stats (character) names statistics display numeric summary variables. Available statistics n, mean_sd, mean_ci, median, median_ci, quantiles, range, geom_mean. denominator (character) chooses percentages calculated. option N, reference population column total used denominator. option n, number non-missing records row column intersection used denominator. omit chosen, percentage omitted. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Summary of Variables — tm_t_summary","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Summary of Variables — tm_t_summary","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Summary of Variables — tm_t_summary","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Summary of Variables — tm_t_summary","text":"","code":"# Preparation of the test case - use `EOSDY` and `DCSREAS` variables to demonstrate missing data. data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADSL$EOSDY[1] <- NA_integer_ }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] app <- init( data = data, modules = modules( tm_t_summary( label = \"Demographic Table\", dataname = \"ADSL\", arm_var = choices_selected(c(\"ARM\", \"ARMCD\"), \"ARM\"), add_total = TRUE, summarize_vars = choices_selected( c(\"SEX\", \"RACE\", \"BMRKR2\", \"EOSDY\", \"DCSREAS\", \"AGE\"), c(\"SEX\", \"RACE\") ), useNA = \"ifany\" ) ) ) #> Initializing tm_t_summary #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary_by.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"module produces table summarize variables row groups.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary_by.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"","code":"tm_t_summary_by( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, by_vars, summarize_vars, id_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, subset = \"USUBJID\"), selected = \"USUBJID\", fixed = TRUE), paramcd = NULL, add_total = TRUE, total_label = default_total_label(), parallel_vars = FALSE, row_groups = FALSE, useNA = c(\"ifany\", \"no\"), na_level = default_na_str(), numeric_stats = c(\"n\", \"mean_sd\", \"median\", \"range\"), denominator = teal.transform::choices_selected(c(\"n\", \"N\", \"omit\"), \"omit\", fixed = TRUE), drop_arm_levels = TRUE, drop_zero_levels = TRUE, pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary_by.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable(s) results table. two elements selected arm_var, second variable nested first variable. by_vars (teal.transform::choices_selected()) object available choices preselected option variable names used split summary rows. summarize_vars (teal.transform::choices_selected()) names variables summarized. id_var (teal.transform::choices_selected()) object specifying variable name subject id. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). parallel_vars (logical) whether summarized variables arranged columns. Can set TRUE chosen analysis variables numeric. row_groups (logical) whether summarized variables arranged row groups. useNA (character) whether missing data (NA) displayed level. na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). numeric_stats (character) names statistics display numeric summary variables. Available statistics n, mean_sd, mean_ci, median, median_ci, quantiles, range, geom_mean. denominator (character) chooses percentages calculated. option N, reference population column total used denominator. option n, number non-missing records row column intersection used denominator. omit chosen, percentage omitted. drop_arm_levels (logical) whether drop unused levels arm_var. TRUE, arm_var levels set used dataname dataset. FALSE, arm_var levels set used parentname dataset. dataname parentname , drop_arm_levels set TRUE user input parameter ignored. drop_zero_levels (logical) whether rows zero counts columns removed table. pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary_by.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary_by.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary_by.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_summary_by.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Summarize Variables by Row Groups — tm_t_summary_by","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADLB <- tmc_ex_adlb }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADLB <- data[[\"ADLB\"]] app <- init( data = data, modules = modules( tm_t_summary_by( label = \"Summary by Row Groups Table\", dataname = \"ADLB\", arm_var = choices_selected( choices = variable_choices(ADSL, c(\"ARM\", \"ARMCD\")), selected = \"ARM\" ), add_total = TRUE, by_vars = choices_selected( choices = variable_choices(ADLB, c(\"PARAM\", \"AVISIT\")), selected = c(\"AVISIT\") ), summarize_vars = choices_selected( choices = variable_choices(ADLB, c(\"AVAL\", \"CHG\")), selected = c(\"AVAL\") ), useNA = \"ifany\", paramcd = choices_selected( choices = value_choices(ADLB, \"PARAMCD\", \"PARAM\"), selected = \"ALT\" ) ) ) ) #> Initializing tm_t_summary_by #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_tte.html","id":null,"dir":"Reference","previous_headings":"","what":"teal Module: Time-To-Event Table — tm_t_tte","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"module produces time--event analysis summary table, consistent TLG Catalog template TTET01 available .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_tte.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"","code":"tm_t_tte( label, dataname, parentname = ifelse(inherits(arm_var, \"data_extract_spec\"), teal.transform::datanames_input(arm_var), \"ADSL\"), arm_var, arm_ref_comp = NULL, paramcd, strata_var, aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVAL\"), \"AVAL\", fixed = TRUE), cnsr_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"CNSR\"), \"CNSR\", fixed = TRUE), conf_level_coxph = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), conf_level_survfit = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order = TRUE), time_points, time_unit_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname, \"AVALU\"), \"AVALU\", fixed = TRUE), event_desc_var = teal.transform::choices_selected(\"EVNTDESC\", \"EVNTDESC\", fixed = TRUE), add_total = FALSE, total_label = default_total_label(), na_level = default_na_str(), pre_output = NULL, post_output = NULL, basic_table_args = teal.widgets::basic_table_args(), decorators = NULL )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_tte.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"label (character) menu item label module teal app. dataname (character) analysis data used teal module. parentname (character) parent analysis data used teal module, usually refers ADSL. arm_var (teal.transform::choices_selected()) object available choices preselected option variable names can used arm_var. defines grouping variable results table. arm_ref_comp (list) optional, specified must named list element corresponding arm variable ADSL element must another list (possibly delayed teal.transform::variable_choices() delayed teal.transform::value_choices() elements named ref comp defined default reference comparison arms arm variable changed. paramcd (teal.transform::choices_selected()) object available choices preselected option parameter code variable dataname. strata_var (teal.transform::choices_selected()) names variables stratified analysis. aval_var (teal.transform::choices_selected()) object available choices pre-selected option analysis variable. cnsr_var (teal.transform::choices_selected()) object available choices preselected option censoring variable. conf_level_coxph (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). conf_level_survfit (teal.transform::choices_selected()) object available choices pre-selected option confidence level, within range (0, 1). time_points (teal.transform::choices_selected()) object available choices preselected option time points can used tern::surv_timepoint(). time_unit_var (teal.transform::choices_selected()) object available choices pre-selected option time unit variable. event_desc_var (character teal.transform::data_extract_spec()) variable name event description information, optional. add_total (logical) whether include column total number patients. total_label (string) string display total column/row label column/row enabled (see add_total). Defaults \"Patients\". set new default total_label apply modules, run set_default_total_label(\"new_default\"). na_level (string) used replace NA empty values character factor variables data. Defaults \"\". set default na_level apply modules, run set_default_na_str(\"new_default\"). pre_output (shiny.tag) optional, text placed output put output context. example title. post_output (shiny.tag) optional, text placed output put output context. example shiny::helpText() elements useful. basic_table_args (basic_table_args) optional object created teal.widgets::basic_table_args() settings module table. argument merged option teal.basic_table_args default module arguments (hard coded module body). details, see vignette: vignette(\"custom-basic-table-arguments\", package = \"teal.widgets\"). decorators \" (list teal_transform_module, named list teal_transform_module \" NULL) optional, NULL, decorator tables plots included module. named list teal_transform_module, decorators applied respective output objects. Otherwise, decorators applied objects, equivalent using name default. See section \"Decorating Module\" details.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_tte.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"teal_module object.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_tte.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"core functionality module based tern::coxph_pairwise(), tern::surv_timepoint(), tern::surv_time() tern package. arm stratification variables taken parentname data. following variables used module: AVAL: time event CNSR: 1 record AVAL censored, 0 otherwise PARAMCD: variable used filter endpoint (e.g. OS). filtering PARAMCD one observation per patient expected","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_tte.html","id":"decorating-module","dir":"Reference","previous_headings":"","what":"Decorating Module","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"module generates following objects, can modified place using decorators: table (TableTree - output rtables::build_table) additional details examples decorators, refer vignette vignette(\"decorate-modules-output\", package = \"teal\") teal_transform_module() documentation.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_tte.html","id":"examples-in-shinylive","dir":"Reference","previous_headings":"","what":"Examples in Shinylive","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"example-1 Open Shinylive","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/tm_t_tte.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"teal Module: Time-To-Event Table — tm_t_tte","text":"","code":"data <- teal_data() data <- within(data, { ADSL <- tmc_ex_adsl ADTTE <- tmc_ex_adtte }) join_keys(data) <- default_cdisc_join_keys[names(data)] ADSL <- data[[\"ADSL\"]] ADTTE <- data[[\"ADTTE\"]] arm_ref_comp <- list( ACTARMCD = list( ref = \"ARM B\", comp = c(\"ARM A\", \"ARM C\") ), ARM = list( ref = \"B: Placebo\", comp = c(\"A: Drug X\", \"C: Combination\") ) ) app <- init( data = data, modules = modules( tm_t_tte( label = \"Time To Event Table\", dataname = \"ADTTE\", arm_var = choices_selected( variable_choices(ADSL, c(\"ARM\", \"ARMCD\", \"ACTARMCD\")), \"ARM\" ), arm_ref_comp = arm_ref_comp, paramcd = choices_selected( value_choices(ADTTE, \"PARAMCD\", \"PARAM\"), \"OS\" ), strata_var = choices_selected( variable_choices(ADSL, c(\"SEX\", \"BMRKR2\")), \"SEX\" ), time_points = choices_selected(c(182, 243), 182), event_desc_var = choices_selected( variable_choices(ADTTE, \"EVNTDESC\"), \"EVNTDESC\", fixed = TRUE ) ) ) ) #> Initializing tm_t_tte #> Initializing reporter_previewer_module if (interactive()) { shinyApp(app$ui, app$server) }"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/validate_arm.html","id":null,"dir":"Reference","previous_headings":"","what":"Check if vector is valid as to be used as a treatment arm variable — validate_arm","title":"Check if vector is valid as to be used as a treatment arm variable — validate_arm","text":"Check vector valid used treatment arm variable","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/validate_arm.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Check if vector is valid as to be used as a treatment arm variable — validate_arm","text":"","code":"validate_arm(arm_vec)"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/validate_arm.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Check if vector is valid as to be used as a treatment arm variable — validate_arm","text":"arm_vec vector validated","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/validate_arm.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Check if vector is valid as to be used as a treatment arm variable — validate_arm","text":"validate error returned vector factor detailed error message entries empty strings","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/validate_standard_inputs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Validate standard input values for a teal module — validate_standard_inputs","text":"","code":"validate_standard_inputs( adsl, adslvars = character(0), anl, anlvars = character(0), need_arm = TRUE, arm_var, ref_arm, comp_arm, min_n_levels_armvar = 1L, max_n_levels_armvar = 100L, min_nrow = 1 )"},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/reference/validate_standard_inputs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Validate standard input values for a teal module — validate_standard_inputs","text":"adsl data.frame subject-level data adslvars required variables ADSL anl data.frame analysis data anlvars required variables ANL need_arm flag indicating whether grouping variable arm_var required can optionally NULL. arm_var character name grouping variable, typically arm ref_arm character name reference level arm_var comp_arm character name comparison level arm_var min_n_levels_armvar minimum number levels grouping variable arm_var. Defaults 1, NULL minimum. max_n_levels_armvar maximum number levels grouping variable arm_var. Use NULL maximum. min_nrow minimum number observations ADSL ANL","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"enhancements-0-9-1-9042","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.9.1.9042","text":"Added teal.logger functionality logging changes shiny inputs modules. Introduced ylim parameter tm_g_km module controls width y-axis. Added functionality tm_t_events_patyear split columns multiple (nested) variables via arm_var argument. Added arguments arm_var_labels template_summary show_arm_var_labels tm_t_summary allow user display arm variable (arm_var) labels table header. Added argument stats modules tm_g_forest_rsp tm_g_forest_tte allow users specify statistics include table. Added argument riskdiff modules tm_g_forest_rsp tm_g_forest_tte allow users add risk difference table column. Added count_dth count_wd parameters tm_t_events_summary select/deselect “Total number deaths” “Total number patients withdrawn study due AE” rows, respectively. options correspond “Count deaths” “Count withdrawals due AE” checkboxes available module run.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-9-1-9042","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.9.1.9042","text":"Removed Show Warnings modals modules. Clarified documentation specifying whether multiple values can selected arm_var argument module. Replaced use rtables::add_colcounts() function show_colcounts argument basic_table(). Began deprecation cycle show_labels argument template_summary effect tm_t_summary module. Replaced instances deprecated strata argument tern::control_lineplot_vars() group_var.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"bug-fixes-0-9-1-9042","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.9.1.9042","text":"Fixed bug creating modules delayed_data teal.transform::all_choices.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"tealmodulesclinical-091","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.9.1","title":"teal.modules.clinical 0.9.1","text":"CRAN release: 2024-04-27","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"enhancements-0-9-1","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.9.1","text":"Updated tm_g_forest_rsp tm_g_forest_tte use refactored version g_forest. Plots now displayed ggplot objects instead grob objects. Added parameters font_size rel_width_forest control font size width plot relative table, respectively. Updated tm_t_summary_by allow NULL input paramcd argument. Updated tm_g_km use refactored version g_km. Plots now displayed ggplot objects instead grob objects. Added parameters rel_height_plot, font_size, control_annot_surv_med, control_annot_coxph control height plot relative table, font size, median survival time table size, Cox-PH table size, respectively. Added control argument tm_t_binary_outcome control settings analysis (methods, confidence intervals, odds ratios) within module.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-9-1","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.9.1","text":"Replaced instances deprecated na_level argument tern functions na_str. Replaced argument/list element name strata instead strat tern function calls following deprecation argument/name within tern. Removed formatters dependencies replaced use functions relating variable labels functions teal.data.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"tealmodulesclinical-090","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.9.0","title":"teal.modules.clinical 0.9.0","text":"CRAN release: 2024-02-23","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"breaking-changes-0-9-0","dir":"Changelog","previous_headings":"","what":"Breaking Changes","title":"teal.modules.clinical 0.9.0","text":"Adapted modules use teal_data objects. Module arguments previously accepted inputs teal.transform::choices_selected() teal.transform::data_extract_spec() now accept input teal.transform::choices_selected(). affected modules : tm_a_gee, tm_a_mmrm, tm_g_ci, tm_g_forest_rsp, tm_g_forest_tte, tm_g_ipp, tm_g_km, tm_g_lineplot, tm_g_pp_adverse_events, tm_g_pp_patient_timeline, tm_g_pp_therapy, tm_g_pp_vitals, tm_t_abnormality, tm_t_abnormality_by_worst_grade, tm_t_ancova, tm_t_binary_outcome, tm_t_coxreg, tm_t_events, tm_t_events_by_grade, tm_t_events_patyear, tm_t_events_summary, tm_t_exposure, tm_t_logistic, tm_t_mult_events, tm_t_pp_basic_info, tm_t_pp_laboratory, tm_t_pp_medical_history, tm_t_pp_prior_medication, tm_t_shift_by_arm, tm_t_shift_by_arm_by_worst, tm_t_shift_by_grade, tm_t_smq, tm_t_summary, tm_t_summary_by, tm_t_tte","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"enhancements-0-9-0","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.9.0","text":"Updated documentation vignettes demonstrate method pass teal_data object teal::init(). Simplify examples vignettes code removing package prefixes possible. Added parameter sort_freq_col tm_t_events allow user select column use sorting decreasing frequency. Added parameter incl_overall_sum tm_t_events allow user choose whether overall summary rows included top table. Updated documentation vignettes demonstrate method pass teal_data object teal::init(). Added default_total_label set_default_total_label functions get set default total column label (total_label) modules. Implemented tern::default_na_str tern::set_default_na_str functions get set default missing value replacement string (na_level) modules.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"bug-fixes-0-9-0","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.9.0","text":"Fixed bug tm_g_lineplot forcing module initialize table. Fixes partial matching.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-9-0","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.9.0","text":"Deprecated aval argument tm_t_pp_laboratory tm_g_pp_vitals replaced aval_var argument. Deprecated avalu argument tm_t_pp_laboratory replaced avalu_var argument. Deprecated base_var argument tm_g_ipp, tm_t_shift_by_arm, template_shift_by_arm_by_worst replaced baseline_var argument. Specified minimal version package dependencies. Replaced usage deprecated summarize_vars function analyze_vars. Reduced package dependencies (removed tidyr, rlang, magrittr styler). Introduced tests partial matching.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"enhancements-0-8-16","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.16","text":"Added informative error message grade mapping error occurs tm_t_abnormality_by_worst_grade. Fixed label indentation tm_t_abnormality_by_worst_grade. Added total_label argument enable customization “Patients” column/row label following modules: tm_a_mmrm, tm_t_abnormality, tm_t_abnormality_by_worst_grade, tm_t_binary_outcome, tm_t_events, tm_t_events_by_grade, tm_t_events_patyear, tm_t_events_summary, tm_t_exposure, tm_t_mult_events, tm_t_shift_by_arm, tm_t_shift_by_arm_worst, tm_t_shift_by_grade, tm_t_smq, tm_t_summary, tm_t_summary_by, tm_t_tte. Increased default width tm_g_forest_tte plot prevent overlapping text. Improved default annotation table sizing tm_g_km. Refactored tm_t_exposure display “total” row last row table instead summary row. Added parameters add_total_row set whether total row displayed total_row_label set total row label. Updated tm_t_events maintain indentation pruning. Updated default reference/comparison arm level selection work arm variable levels filtered . Updated tm_t_coxreg drop factor covariate variable levels present avoid errors filtering. Updated tm_t_pp_basic_info, tm_t_pp_medical_history, tm_g_pp_therapy, tm_g_pp_adverse_events, tm_t_pp_laboratory print patient ID table. Updated tm_t_pp_basic_info, tm_g_pp_therapy, tm_g_pp_adverse_events, tm_t_pp_laboratory use rlistings print data neatly reports. Updated tm_g_lineplot allow user remove interval plot. Updated documentation vignettes demonstrate method pass teal_data object teal::init().","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"bug-fixes-0-8-16","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.16","text":"Fixed bug tm_t_coxreg preventing table displayed covariates selected.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-8-16","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.16","text":"Updated control_incidence_rate parameter names tm_t_events_patyear time_unit_input time_unit_output input_time_unit num_pt_year, respectively, parameter names changed tern. Hid datasets used patient profile modules filter panel. Replaced datanames = \"\" parameter datasets used internally module.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"breaking-changes-0-8-15","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"teal.modules.clinical 0.8.15","text":"Replaced chunks simpler qenv class. Replaced datasets argument containing FilteredData new arguments data (tdata object) filter_panel_api (FilterPanelAPI).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"enhancements-0-8-15","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.15","text":"Replaced synthetic_cdisc_data refactored synthetic_cdisc_dataset function speed dataset loading tests/examples. Added new GEE module tm_a_gee. Added interface selecting interaction term tm_t_ancova. Updated encoding input checks use shinyvalidate::InputValidator better UI experience. Previously used shiny::validate. Added option tm_a_mmrm allow Kenward-Roger adjustments standard errors p-values. Added option choose facet scale options tm_g_barchart_simple. Added label parameter cs_to_select_spec/cs_to_des_select cs_to_filter_spec/cs_to_des_filter allow user customize label printed selection field. Updated tm_t_coxreg module refactoring summarize_coxreg tern fix indentation. Updated tm_t_exposure module use new function analyze_patients_exposure_in_cols fix table structure.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"bug-fixes-0-8-15","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.15","text":"Fixed bug causing overlapping bars tm_g_barchart_simple. Fixed bug figures svg format. Fixed bug tm_t_summary tm_t_summary_by preventing users specifying numeric_stats argument.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-8-15","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.15","text":"Updated package Suggests use scda.2022 rather scda.2021. Removed unused argument param tm_g_pp_vitals. Removed optimizer choice tm_a_mmrm since can always use automatically determined optimizer. Created datasets use examples/tests adsl, adae, adaette, adcm, adeg, adex, adlb, admh, adqs, adrs, adtte, advs. datasets stored data folder accessible via tmc_ex_* prefix. Updated examples tests use datasets teal.modules.clinical package instead scda datasets. Updated tests use testthat 3rd edition replaced applicable tests snapshot testing. Implemented lubridate package date variables internal data. Changed default value plot_width tm_g_forest_rsp prevent clutter.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"enhancements-0-8-14","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.14","text":"Updated synthetic data tests version rcd_2022_02_28. Updated test files tests/testthat/ synthetic_cdisc_data(\"2022_02_28\") Reverted missing data checkbox tm_t_summary (encoding filtering separate). Implemented new widget allows dragging dropping select comparison groups. Added teal.reporter functionality modules. Enhanced tm_t_pp_medical_history module use table_with_settings module return rtables object. Implemented nestcolor examples, refactored tm_g_barchart_simple allow use nestcolor. Added descriptive title/labels visit name subtitle tm_g_ci. Updated tm_a_mmrm column name deselecting treatment “obs” “Patients”, added subtitles footnotes. Added title parameter category subtitle tm_t_exposure, cleaned labels. Added titles worse flag variable subtitles tm_t_shift_by_grade tm_t_shift_by_arm_by_worst. Added footnote tm_t_events_patyear CI method. Added subtitle footnotes tm_g_km. Added Stratified Analysis CI method option panel tm_t_binary_outcome. Added validation covariate/visit conflicts tm_a_mmrm. Remove unnecessary brackets header tm_t_exposure. Hid footnotes tm_g_km tm_t_tte “Compare Treatments” .","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"bug-fixes-0-8-14","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.14","text":"Fixed bug tm_g_barchart_simple prevented display graph. Fixed broken example tm_t_abnormality_by_worst_grade. Fixed bug tm_a_mmrm prevented table headers displaying. Fixed bug tm_g_forest_rsp deselecting endpoint. Fixed bug tm_t_binary_outcome crashed app deselecting paramcd. Fixed teal.reporter card names tm_t_smq. Fixed bug tm_t_shift_by_arm_by_worst adding validations choosing different endpoint values. Fixed bug tm_t_coxreg preventing footnotes displaying univariate models.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-8-14","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.14","text":"Added nestcolor dependency replaced deprecated function tern::color_palette nestcolor::color_palette.","code":""},{"path":[]},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"tm_g_pp_adverse_events-0-8-13","dir":"Changelog","previous_headings":"Enhancements","what":"tm_g_pp_adverse_events","title":"teal.modules.clinical 0.8.13","text":"Updated position labels. Updated plot render color legend.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"tm_t_summary_by-0-8-13","dir":"Changelog","previous_headings":"Enhancements","what":"tm_t_summary_by","title":"teal.modules.clinical 0.8.13","text":"Enhanced module support geometric mean encoding panel.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"tm_t_summary-0-8-13","dir":"Changelog","previous_headings":"Enhancements","what":"tm_t_summary","title":"teal.modules.clinical 0.8.13","text":"Updated added footnote. Enhanced module support geometric mean encoding panel. Updated module display checkboxes numeric variables statistics numeric variables part selected. Updated validations warn users using dataset non unique identifiers selecting variables non supported types (.e. Date, POSIXt). Added checkbox remove column generated missing values.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"other-modules-0-8-13","dir":"Changelog","previous_headings":"Enhancements","what":"Other modules","title":"teal.modules.clinical 0.8.13","text":"Updated tm_t_binary_outcome enable option apply continuity correction Newcombe method. Simplified show R code tm_g_pp_patient_timeline module. Improved names code chunks shown Debug Info. Improved validation treatment variable factor.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"bug-fixes-0-8-13","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.13","text":"Fixed summarize_logistic implementation broken empty string error. upstream. _NA_ new standard flag allow pivot empty entries data frames. Took @title tm_t_binary_outcome.R producing warning. Updated validation account error selecting single variable tm_g_pp_patient_timeline module.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-8-13","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.13","text":"Added pkgdown template documentation. Updated package authors.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-8-12","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.12","text":"Changed input Covariates tm_t_coxreg.R track user input reflect order table.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"new-features-0-8-12","dir":"Changelog","previous_headings":"","what":"New features","title":"teal.modules.clinical 0.8.12","text":"Added new module tm_t_shift_by_arm_by_worst analysis laboratory abnormalities severe grade flag. Enhanced tm_t_events_patyear include selected parameter title table. Enhanced tm_t_mult_events include selected parameter title table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"enhancements-0-8-12","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.12","text":"Rewrote modules use moduleServer updated calls teal.devel modules also written use moduleServer. Changed way obtaining selection ordered changes teal.devel. Use ordered = TRUE cs_to_des_select cs_to_select_spec return ordered selection. Replaced calls teal::root_modules teal::modules following deprecation teal::root_modules. tm_t_events_summary now allows nested arm_var columns matching outputs tm_t_events. Added validation tm_t_abnormality_by_worst_grade arm_var selected. Enhanced tm_t_binary_outcome include responders response table default. Added subtitle tm_g_forest_tte, tm_t_coxreg, tm_t_binary_outcome listing stratification factors.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"bug-fixes-0-8-12","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.12","text":"Fixed bug prevent processing empty sets data tm_g_forest_rsp.R causing shiny errors runtime. Fixed bug closed Compare Treatments conditional panel marked Combine comparison groups? option conflicted adding column patients tables tm_t_binary_outcome.R tm_t_tte.R.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-8-12-1","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.12","text":"Replaced deprecated rtables::var_labels calls documentation examples. Add import tern.mmrm package change references split tern. Adjusted package imports take account changes teal framework. Ensure consistent vertical order tm_g_pp_patient_timeline output switching absolute relative days.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"breaking-changes-0-8-11","dir":"Changelog","previous_headings":"","what":"Breaking changes","title":"teal.modules.clinical 0.8.11","text":"Updated tm_t_abnormality due changes count_abnormal abnormal argument taking list input now. Changed tm_g_pp_patient_timeline parameter, cmtrt, cmdecod.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"new-features-0-8-11","dir":"Changelog","previous_headings":"","what":"New features","title":"teal.modules.clinical 0.8.11","text":"Added new module tm_t_abnormality_by_worst_grade analysis laboratory test results highest grade post-baseline. Enhanced tm_t_ancova include selected parameter(s), visit(s) analysis variable title table. Added new module tm_g_lineplot creating line plots. Enhanced tm_t_logistic include selected parameter title table. Enhanced tm_g_forest_rsp include selected parameter title table. Enhanced tm_g_forest_tte include selected parameter title table. Enhanced tm_g_pp_patient_timeline bold axes labels integer values axis. Enhanced tm_g_ipp allow users display AVALU title y axis.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"enhancements-0-8-11","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.11","text":"Added support logging logger package added info level logs upon initialization module. Added default_responses argument tm_t_binary_outcome tm_g_forest_rsp allow user specify default selected responses possible response levels. Updated tm_t_binary_outcome show selected responses output table selecting “Show Selected Response Categories”. Added rsp_table argument tm_t_binary_outcome allow user initialize module matching RSPT01 STREAM template. Added support custom arguments ggplot2::labs ggplot2::theme plot based modules. Added support custom arguments rtables::basic_table table based modules. Updated tm_t_binary_outcome enable option apply continuity correction Wilson method.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-8-11","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.11","text":"Updated required R version >= 3.6. Refactored calls defunct teal.devel::data_extract_input calls replacement teal.devel::data_extract_ui. Updated modules use new data_merge_module interface provided teal.devel removed usage now deprecated function teal.devel::get_input_order. Updated tm_t_binary_outcome module add template removed now deprecated module tm_t_rsp. Removed utils.nest dependency replaced calls checkmate equivalents.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"bug-fixes-0-8-11","dir":"Changelog","previous_headings":"","what":"Bug Fixes","title":"teal.modules.clinical 0.8.11","text":"Fixed bug tm_g_pp_therapy cmstdy cmendy argument type integer causes plot crash.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"new-features-0-8-10","dir":"Changelog","previous_headings":"","what":"New features","title":"teal.modules.clinical 0.8.10","text":"Added new module tm_t_smq analysis adverse events Standardized MedDRA Query. Added new module tm_t_shift_by_grade analysis grade laboratory abnormalities. Added new module tm_t_exposure analysis duration exposure risk management plan. Added new module tm_t_shift_by_arm can display shift table ECG interval data.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"bug-fixes-0-8-10","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.10","text":"Corrected tm_a_mmrm able consider treatment variable interactions. Fixed tm_t_binary_outcome tm_t_rsp choose correct CI estimation method Proportions Difference Stratified Analysis (.e. Wald-type confidence interval CMH weights).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"enhancements-0-8-10","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.10","text":"Added validation checks tm_t_rsp tm_t_binary_outcome stratification errors applied filters. Added tm_g_km validation check plot tables font size. Enhanced tm_g_km add selected paramcd plot title. tm_t_events now can display layouts two nested column treatment variables. options pruning sorting available. Exported package helper functions. Updated tm_t_events_by_grade display grading groups nested columns col_by_grade option support pruning sorting options like tm_t_events. Used format_count_fraction fix formatting inconsistency tm_t_events_summary. Updated count_occurrences vars argument tm_t_shift_by_grade. Updated tm_t_pp_laboratory display 4 decimals default. Updated tm_t_events_by_grade use trim_levels_in_group split function instead trim_rows function. Added table title tm_t_tte. Added table titles tm_t_rsp tm_t_binary_outcome.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-8-10","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.10","text":"Updated LICENCE README new package references. Added error_on_lint: TRUE .lintr. Removed insert_rrow updated usage count_patients_by_flags tm_t_events_summary. Changed package calls functions dplyr package. functions now fully specified (e.g. dplyr::filter).","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"new-features-0-8-9","dir":"Changelog","previous_headings":"","what":"New features","title":"teal.modules.clinical 0.8.9","text":"Added capability remember order user input encoding UI elements. Inputs marked double arrow icon tracking enabled. affected modules : tm_t_summary, tm_t_summary_by, tm_g_forest_rsp, tm_g_forest_tte, tm_t_events_summary, tm_t_abnormality, tm_t_mult_events. Added new argument numeric_stats tm_t_summary tm_t_summary_by control displayed summary statistics numeric variables. Added new argument drop_zero_levels tm_t_summary_by can drop rows zeros result table.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"enhancements-0-8-9","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.9","text":"Split tm_g_patient_profile tabs 8 separate new modules. Added option select patient ID filter panel modules patient profile. Added validation tm_g_patient_timeline plot empty. Enhanced tm_a_mmrm work without treatment variable. Added option choose number decimal places rounding tm_t_pp_laboratory. Added check box tm_g_pp_patient_timeline hiding/showing relative study days x-axis. Added title patient’s id plots patient profile modules. Made gray error message tm_g_forest_tte informative deselecting Endpoint column left-hand encoding panel. Added twenty-fifth seventy-fifth quantile summary statistics tm_t_summary. Added interaction p-value column tm_t_coxreg. Added validation tm_t_ancova selected covariate variables contain one level. Added validation tm_t_events_patyear events variable empty. Changed font size input description tm_g_km precisely describe controls. Enhanced tm_t_logistic interaction choices depend selected covariates. Enhanced tm_t_rsp strata input visible comparing treatments.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"bug-fixes-0-8-9","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.9","text":"Fixed Get R Code output tm_t_pp_laboratory return identical HTML formatted table displayed app. Added validation tm_t_coxreg ensure treatment, strata covariate variables overlap. Limited label repel feature tm_g_pp_patient_timeline X-axis consistent look. Updated tm_t_summary_by paramcd required analyzing ADSL variables. Updated tm_t_coxreg can work covariate selected. Updated tm_a_mmrm can work treatment variable selected. Updated tm_g_forest_tte total number events also shown table. Updated tm_t_events_summary work pooled studies. Updated validation level tm_t_coxreg. Updated validation level tm_t_logistic. Added validation tm_t_binary_outcome tm_t_rsp ensure strata variable contains one level selecting one strata variable. Updated warning message deselecting statistics tm_t_summary tm_t_summary_by explain need select least one statistic.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"enhancements-0-8-8","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.8","text":"Added option download expand tables. tm_g_km added support downloading images updated x-axis label show title case. Added slider font size plots. Added persistence selected table lengths. timeline plot now supports edge cases. vitals tab, removed unused label text legend, updated plot display stable colors per levels, cleared x-axis limit fixed legend update filtering. Also added note clarify supported horizontal lines cases. Updated adverse events tab show warning message instead empty plot data empty. Fixed PARAMCD selected levels current patient. Updated pre-processing code inside template_tte dataset without events still produces table. Updated code use correct denominator duration response endpoints. Modified parameter arm_var accept one column. selecting two columns arm_var, second variable nest first one. Added argument show_labels template_summary show label single summary variable table. Added new parameter conf_arg tm_t_rsp consistent efficacy modules. Added validation statement tm_g_ipp module print message deselecting Timepoint Variable drop-. Removed header definition tm_g_forest_rsp tm_g_forest_tte now default header g_forest. Fixed validation statement tm_t_coxreg models without strata using likelihood tests return result. Clarified functionality drop_arm_levels tm_t_summary tm_t_summary_by. encodings panel, checkbox show parent dataset analysis dataset different.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-8-8","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.8","text":"Replaced remaining two observe function calls observeEvent optimize performance. Fixed grammar “Select patient’s id” error message tm_g_patient_profile. Fixed font_size default templates 12L instead vector 3 integers cleaned associated unnecessary code. Fixed deprecated function warning tm_g_barchart_simple. Fixed subgroup_var definition truncation tm_g_forest_rsp tm_g_forest_tte. Clarified labeling related regression type encoding panel tm_t_coxreg.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"bug-fixes-0-8-8","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.8","text":"Added validation case filtering rows therapy tab tm_g_patient_profile. Updated internals modules read data correct field filter_spec objects. Fixed reactivity filter panel PARAMCD variable levels input tm_g_patient_profile vitals tab plot get reset filtering. Updated vitals plot tab tm_g_patient_profile drop NA entries plot. Updated tm_t_coxreg take values account. Added check tm_t_coxreg interactions univariate models multivariate models. Updated tm_t_events_summary work pooled studies.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"new-module-0-8-7","dir":"Changelog","previous_headings":"","what":"New Module","title":"teal.modules.clinical 0.8.7","text":"Added new module tm_g_patient_profile profile patients based predefined categories. Added new module tm_g_ipp individual patient plots.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"enhancements-0-8-7","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.7","text":"Added argument drop_arm_levels safety modules. allows removal columns based factor levels found filtered data. Updated tm_g_km allow plot failure probability y-axis, tick interval selection x-axis option create plot without confidence interval ribbon (new default). Added argument time_unit_var template_g_km add time unit x-axis label.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-8-7","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.7","text":"Removed redundant Analysis Data: label Encodings Panel. Removed limit requiring 15 fewer columns tabulation modules. New upper threshold 100 columns. Decreased lower limit number observations required modules. Safety tables require least one record. Requirements efficacy outputs per treatment group: tm_a_mmrm requires five records, tm_t_logistic tm_t_coxreg require two records, remaining modules require least one record per treatment group. graphs, lower threshold two records. Removed argument cnsr_val tm_t_events_patyear added new argument events_var. arm_ref_comp_observer include parentname argument. Show R code include datasets retrieved data_extract_spec objects. Refactored stringr dependency patient profile module. Added missing table calls chunks tm_t_events tm_t_events_by_grade.","code":""},{"path":[]},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"new-features-0-8-6","dir":"Changelog","previous_headings":"","what":"New Features","title":"teal.modules.clinical 0.8.6","text":"Added new module tm_g_ci confidence interval plots. Added new module tm_t_ancova analysis variance summary tables. Added new module tm_t_mult_events multi-event tables.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"enhancements-0-8-6","dir":"Changelog","previous_headings":"","what":"Enhancements","title":"teal.modules.clinical 0.8.6","text":"Refactored modules using redesigned rtables tern packages. Enhanced modules. now take advantage data_extract_spec data_merge_module functionality teal. Reduced clutter repeated datasets encodings panels. Updated modules use OptionalSelectInput conf_level.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"miscellaneous-0-8-6","dir":"Changelog","previous_headings":"","what":"Miscellaneous","title":"teal.modules.clinical 0.8.6","text":"Added vignette substitute can helpful developing analysis template functions teal modules.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"bug-fixes-0-8-6","dir":"Changelog","previous_headings":"","what":"Bug fixes","title":"teal.modules.clinical 0.8.6","text":"Updated tm_t_events module use user’s non-default choices prune_freq prune_diff.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"tealmodulesclinical-085","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.8.5","title":"teal.modules.clinical 0.8.5","text":"graph modules now accept plot_width argument specifies plot width renders slider adjust width interactively module. FilteredData object now passed arm_ref_comp_observer modules now support nested lists containing delayed_data objects. Replace plot_with_height module new plot_with_settings module. Update examples use code argument inside cdisc_dataset.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"tealmodulesclinical-084","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.8.4","title":"teal.modules.clinical 0.8.4","text":"Extend tm_t_coxreg optionally produce univariate Cox regressions. Updated tm_t_binary_outcome display Odds Ratio estimates, include new methods CIs p-values display summary individual response categories. Updated tm_t_tte optionally compare arms, removed conf_level argument. Updated tm_g_km optionally compare arms. Extend tm_g_km optionally scale X axis range case one plot. New tm_a_mmrm MMRM analysis. Deprecated tm_t_mmrm (superseded tm_a_mmrm).","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"tealmodulesclinical-083","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.8.3","title":"teal.modules.clinical 0.8.3","text":"New tm_t_coxreg module multi-variable Cox regressions. New tm_t_binary_outcome module. New tm_t_events_patyear module: events rate adjusted patient-year risk table. Remove grade_levels argument tm_t_events_by_grade. Updated response table single arm. New tm_t_abnormality module. Removed get_relabel_call get_relabel_call2 favor teal.devel::get_relabel_call teal.devel::get_anl_relabel_call.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"tealmodulesclinical-082","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.8.2","title":"teal.modules.clinical 0.8.2","text":"Add confidence level survfit, coxph, ztest; add confidence type, ties, percentiles tm_t_tte. Optionally use single term tm_t_events tm_t_events_by_grade modules. New tm_t_logistic module. New tm_t_mmrm module. New modules tm_t_summary_by tm_t_events_summary. Add stratified analysis tm_g_forest_tte tm_g_forest_rsp. Add confidence level plotting symbol size options tm_g_forest_rsp tm_g_forest_tte.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"tealmodulesclinical-081","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.8.1","title":"teal.modules.clinical 0.8.1","text":"New tm_t_events tm_t_events_by_grade modules.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"tealmodulesclinical-080","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.8.0","title":"teal.modules.clinical 0.8.0","text":"Optionally show KM CoxPH table tm_g_km.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"tealmodulesclinical-070","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.7.0","title":"teal.modules.clinical 0.7.0","text":"Use teal.devel.","code":""},{"path":"https://insightsengineering.github.io/teal.modules.clinical/main/news/index.html","id":"tealmodulesclinical-060","dir":"Changelog","previous_headings":"","what":"teal.modules.clinical 0.6.0","title":"teal.modules.clinical 0.6.0","text":"Package renamed teal.modules.clinical. Rename tm_t_summarize_variables tm_t_summary. Usage teal::choices_selected() function instead *_var *_var_choices arguments.","code":""}]
![[Experimental]](figures/lifecycle-experimental.svg)
+![[Deprecated]](figures/lifecycle-deprecated.svg)
Please use the