Replace summarize_vars usage with analyze_vars (#114)

Closes #113
insightsengineering · Sep 8, 2023 · f5296f6 · f5296f6
1 parent 6bad07b
commit f5296f6
Show file tree

Hide file tree

Showing 22 changed files with 62 additions and 62 deletions.
diff --git a/book/graphs/other/cig01.qmd b/book/graphs/other/cig01.qmd
@@ -154,7 +154,7 @@ The corresponding table is simply obtained using the `rtables` framework:
 ```{r table6, test = list(table_v6 = "table")}
 lyt <- basic_table() %>%
   split_cols_by(var = "ARMCD") %>%
-  summarize_vars(vars = "AVAL", .stats = c("mean_sd", "median"))
+  analyze_vars(vars = "AVAL", .stats = c("mean_sd", "median"))
 table <- build_table(lyt = lyt, df = adlb)
 table
 ```

diff --git a/book/graphs/other/mng01.qmd b/book/graphs/other/mng01.qmd
@@ -94,7 +94,7 @@ plot
 plot <- g_lineplot(
   df = adlb_f,
   alt_counts_df = adsl_f,
-  control = control_summarize_vars(conf_level = 0.80),
+  control = control_analyze_vars(conf_level = 0.80),
   title = "Plot of Mean and 80% Confidence Limits by Visit",
   subtitle = "Laboratory Test:"
 )

diff --git a/book/tables/adverse-events/aet04_pi.qmd b/book/tables/adverse-events/aet04_pi.qmd
@@ -52,7 +52,7 @@ full_table_aet04_pi <- function(adsl, adae_max) {
       .stats = "unique",
       .labels = "Total number of patients with at least one adverse event"
     ) %>%
-    summarize_vars(
+    analyze_vars(
       "AEDECOD",
       na.rm = FALSE,
       denom = "N_col",
@@ -241,7 +241,7 @@ full_table <- basic_table() %>%
     .stats = "unique",
     .labels = "Total number of patients with at least one adverse event"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     "AEDECOD",
     na.rm = FALSE,
     denom = "N_col",
@@ -298,7 +298,7 @@ full_table <- basic_table() %>%
     .stats = "unique",
     .labels = "Total number of patients with at least one adverse event"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     "AEDECOD",
     na.rm = FALSE,
     denom = "N_col",
@@ -345,7 +345,7 @@ col_counts <- rep(table(adsl$ACTARM), each = length(grade_groups))
 full_table <- basic_table() %>%
   split_cols_by("ACTARM") %>%
   split_cols_by_groups("MAXAETOXGR", groups = grade_groups) %>%
-  summarize_vars(
+  analyze_vars(
     "AEDECOD",
     na.rm = FALSE,
     denom = "N_col",

diff --git a/book/tables/efficacy/dort01.qmd b/book/tables/efficacy/dort01.qmd
@@ -52,7 +52,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .labels = "Responders",
     .stats = "count"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders with subsequent event (%)"),
@@ -68,7 +68,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 2L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders without subsequent event (%)"),
@@ -105,7 +105,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .labels = "Responders",
     .stats = "count"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders with subsequent event (%)"),
@@ -121,7 +121,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 2L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders without subsequent event (%)"),
@@ -160,7 +160,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .labels = "Responders",
     .stats = "count"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders with subsequent event (%)"),
@@ -176,7 +176,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 2L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders without subsequent event (%)"),
@@ -215,7 +215,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     .labels = "Responders",
     .stats = "count"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders with subsequent event (%)"),
@@ -231,7 +231,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 2L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Responders without subsequent event (%)"),

diff --git a/book/tables/efficacy/mmrmt01.qmd b/book/tables/efficacy/mmrmt01.qmd
@@ -128,7 +128,7 @@ baseline_dat <- adqs %>%
 b <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARMCD") %>%
   split_rows_by("AVISIT") %>%
-  summarize_vars("AVAL") %>%
+  analyze_vars("AVAL") %>%
   append_topleft("  Statistics") %>%
   build_table(baseline_dat, alt_counts_df = adsl_sub)
 

diff --git a/book/tables/efficacy/ttet01.qmd b/book/tables/efficacy/ttet01.qmd
@@ -48,7 +48,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(
     var = "ARM", ref_group = "A: Drug X"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients with event (%)")
@@ -62,7 +62,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 1L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients without event (%)"),
@@ -102,12 +102,12 @@ result
 ```{r variant2, test = list(result_v2 = "result")}
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM", ref_group = "A: Drug X") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients with event (%)")
   ) %>%
-  summarize_vars(
+  analyze_vars(
     "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients without event (%)"),
@@ -144,7 +144,7 @@ result
 ```{r variant3, test = list(result_v3 = "result")}
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM", ref_group = "A: Drug X") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients with event (%)")
@@ -158,7 +158,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 1L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients without event (%)"),
@@ -212,7 +212,7 @@ result
 ```{r variant4, test = list(result_v4 = "result")}
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM", ref_group = "A: Drug X") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients with event (%)")
@@ -226,7 +226,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 1L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients without event (%)"),
@@ -271,7 +271,7 @@ result
 ```{r variant5, test = list(result_v5 = "result")}
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM", ref_group = "A: Drug X") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients with event (%)")
@@ -285,7 +285,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 1L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients without event (%)"),
@@ -324,7 +324,7 @@ result
 ```{r variant6, test = list(result_v6 = "result")}
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM", ref_group = "A: Drug X") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients with event (%)")
@@ -338,7 +338,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     indent_mod = 1L,
   ) %>%
   analyze("EVNTDESC") %>%
-  summarize_vars(
+  analyze_vars(
     vars = "is_not_event",
     .stats = "count_fraction",
     .labels = c(count_fraction = "Patients without event (%)"),

diff --git a/book/tables/lab-results/lbt02.qmd b/book/tables/lab-results/lbt02.qmd
@@ -49,7 +49,7 @@ l <- basic_table(show_colcounts = TRUE) %>%
     label_pos = "topleft",
     split_label = obj_label(adlb$AVISIT)
   ) %>%
-  summarize_vars(vars = "AVAL")
+  analyze_vars(vars = "AVAL")
 
 result <- build_table(l,
   df = adlb,

diff --git a/book/tables/other/disclosurest01.qmd b/book/tables/other/disclosurest01.qmd
@@ -113,7 +113,7 @@ lyt <- basic_table(show_colcounts = TRUE) %>%
     split_fun = split_fun
   ) %>%
   summarize_row_groups(label_fstr = "Discontinued Study") %>%
-  summarize_vars(
+  analyze_vars(
     "STDDRS",
     .stats = "count_fraction"
   ) %>%
@@ -166,7 +166,7 @@ var_labels <- c("Age (yr)", "Age group", "Sex", "Race", "Ethnicity")
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(var = "ARM") %>%
   add_overall_col("All Patients") %>%
-  summarize_vars(
+  analyze_vars(
     vars = vars,
     var_labels = var_labels
   )
@@ -203,7 +203,7 @@ var_labels(adsl) <- c(adsl_labels)
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM") %>%
   add_overall_col(label = "All Patients") %>%
-  summarize_vars("COUNTRY") %>%
+  analyze_vars("COUNTRY") %>%
   append_varlabels(adsl, "COUNTRY")
 
 result <- build_table(lyt, adsl)

diff --git a/book/tables/other/ratet01.qmd b/book/tables/other/ratet01.qmd
@@ -33,7 +33,7 @@ anl <- df_explicit_na(anl)
 ```{r variant1, test = list(result_v1 = "result")}
 lyt <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by("ARM", ref_group = "B: Placebo") %>%
-  summarize_vars(
+  analyze_vars(
     "AVAL_f",
     var_labels = "Number of exacerbations per patient",
     .stats = c("count_fraction"),

diff --git a/book/tables/pharmacokinetic/adat02.qmd b/book/tables/pharmacokinetic/adat02.qmd
@@ -93,13 +93,13 @@ lyt_adab_ti <- basic_table(show_colcounts = TRUE) %>%
     var_labels = "Treatment-induced ADA patients with",
     show_labels = "visible"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     "Time to onset of ADA",
     .stats = "median",
     nested = FALSE,
     .labels = c(median = "Median time to onset of ADA (weeks)")
   ) %>%
-  summarize_vars(
+  analyze_vars(
     "Antibody titer units",
     .stats = "range",
     nested = FALSE,

diff --git a/book/tables/pharmacokinetic/pkpt02.qmd b/book/tables/pharmacokinetic/pkpt02.qmd
@@ -37,7 +37,7 @@ lyt <- basic_table() %>%
     label_pos = "topleft",
     split_label = "PK Parameter"
   ) %>%
-  tern::summarize_vars(
+  tern::analyze_vars(
     vars = "AVAL",
     .stats = c("n", "mean_sd", "cv", "geom_mean", "geom_cv", "median", "range"),
     .formats = c(

diff --git a/book/tables/pharmacokinetic/pkpt04.qmd b/book/tables/pharmacokinetic/pkpt04.qmd
@@ -37,7 +37,7 @@ lyt <- basic_table() %>%
     label_pos = "topleft",
     split_label = "PK Parameter"
   ) %>%
-  tern::summarize_vars(
+  tern::analyze_vars(
     vars = "AVAL",
     .stats = c("n", "mean_sd", "cv", "geom_mean", "geom_cv", "median", "range"),
     .formats = c(

diff --git a/book/tables/pharmacokinetic/pkpt06.qmd b/book/tables/pharmacokinetic/pkpt06.qmd
@@ -38,7 +38,7 @@ lyt <- basic_table() %>%
     label_pos = "topleft",
     split_label = "PK Parameter"
   ) %>%
-  tern::summarize_vars(
+  tern::analyze_vars(
     vars = "AVAL",
     .stats = c("n", "mean_sd", "cv", "geom_mean", "geom_cv", "median", "range"),
     .formats = c(

diff --git a/book/tables/pharmacokinetic/pkpt08.qmd b/book/tables/pharmacokinetic/pkpt08.qmd
@@ -38,7 +38,7 @@ lyt <- basic_table() %>%
     label_pos = "topleft",
     split_label = "Treatment Arm"
   ) %>%
-  summarize_vars(
+  analyze_vars(
     vars = "AVAL",
     .stats = c(
       "n", "mean", "sd", "cv",

diff --git a/book/tables/safety/dmt01.qmd b/book/tables/safety/dmt01.qmd
@@ -101,7 +101,7 @@ var_labels <- c(
 result <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(var = "ACTARM") %>%
   add_overall_col("All Patients") %>%
-  summarize_vars(
+  analyze_vars(
     vars = vars,
     var_labels = var_labels
   ) %>%
@@ -125,7 +125,7 @@ var_labels <- c(
 
 result <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(var = "ACTARM") %>%
-  summarize_vars(
+  analyze_vars(
     vars = vars,
     var_labels = var_labels
   ) %>%
@@ -141,14 +141,14 @@ split_fun <- drop_split_levels
 
 result <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(var = "ACTARM") %>%
-  summarize_vars(
+  analyze_vars(
     vars = c("AGE", "SEX", "RACE"),
     var_labels = c("Age", "Sex", "Race")
   ) %>%
   split_rows_by("STRATA1",
     split_fun = split_fun
   ) %>%
-  summarize_vars("BMRKR1") %>%
+  analyze_vars("BMRKR1") %>%
   build_table(adsl)
 
 result
@@ -159,7 +159,7 @@ result
 ```{r variant4, test = list(result_v4 = "result")}
 result <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(var = "ACTARM") %>%
-  summarize_vars(
+  analyze_vars(
     vars = c("AGE", "SEX", "RACE", "DBP", "SBP"),
     var_labels = c(
       "Age (yr)",
@@ -179,7 +179,7 @@ result
 ```{r variant5, test = list(result_v5 = "result")}
 result <- basic_table(show_colcounts = TRUE) %>%
   split_cols_by(var = "ACTARM") %>%
-  summarize_vars(
+  analyze_vars(
     vars = c("AGE", "SEX", "RACE", "BBMISI"),
     var_labels = c(
       "Age (yr)",