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insightsengineering · Sep 25, 2023 · 7f56518 · 7f56518
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diff --git a/book/tables/pharmacokinetic/pkct01.qmd b/book/tables/pharmacokinetic/pkct01.qmd
@@ -10,140 +10,6 @@ subtitle: Summary Concentration Table
 ::: panel-tabset
 ## Data Setup
 
-```{r setup, message=FALSE}
-#| code-fold: show
-
-library(scda)
-library(dplyr)
-library(tern)
-
-adsl <- synthetic_cdisc_dataset("latest", "adsl") %>%
-  filter(ACTARM == "A: Drug X")
-adpc <- synthetic_cdisc_dataset("latest", "adpc") %>%
-  filter(ACTARM == "A: Drug X", PARAM == "Plasma Drug X")
-
-# Setting up the data
-adpc_1 <- adpc %>%
-  mutate(
-    NFRLT = as.factor(NFRLT),
-    AVALCAT1 = as.factor(AVALCAT1)
-  ) %>%
-  select(NFRLT, ACTARM, VISIT, AVAL, PARAM, AVALCAT1) %>%
-  var_relabel(NFRLT = "Nominal Time from First Dose (hr)")
-
-# Row structure
-lyt_rows <- basic_table() %>%
-  split_rows_by(
-    var = "ACTARM",
-    split_fun = drop_split_levels,
-    split_label = "Treatment Group",
-    label_pos = "topleft"
-  ) %>%
-  add_rowcounts(alt_counts = TRUE) %>%
-  split_rows_by(
-    var = "VISIT",
-    split_fun = drop_split_levels,
-    split_label = "Visit",
-    label_pos = "topleft"
-  ) %>%
-  split_rows_by(
-    var = "NFRLT",
-    split_fun = drop_split_levels,
-    split_label = obj_label(adpc_1$NFRLT),
-    label_pos = "topleft",
-    child_labels = "hidden"
-  )
-```
-
-## Standard Table (Stats in Columns)
-
-```{r variant1, test = list(result_v1 = "result")}
-lyt <- lyt_rows %>%
-  analyze_vars_in_cols(
-    vars = c("AVAL", "AVALCAT1", rep("AVAL", 8)),
-    .stats = c("n", "n_blq", "mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max"),
-    .formats = c(
-      n = "xx.", n_blq = "xx.", mean = format_sigfig(3), sd = format_sigfig(3), cv = "xx.x", median = format_sigfig(3),
-      geom_mean = format_sigfig(3), geom_cv = "xx.x", min = format_sigfig(3), max = format_sigfig(3)
-    ),
-    .labels = c(
-      n = "n", n_blq = "Number\nof\nLTRs/BLQs", mean = "Mean", sd = "SD", cv = "CV (%) Mean",
-      geom_mean = "Geometric Mean", geom_cv = "CV % Geometric Mean", median = "Median", min = "Minimum", max = "Maximum"
-    ),
-    na_level = "NE",
-    .aligns = "decimal"
-  )
-
-result <- build_table(lyt, df = adpc_1, alt_counts_df = adsl) %>% prune_table()
-
-# Decorating
-main_title(result) <- "Summary of PK Concentrations by Nominal Time and Treatment: PK Evaluable"
-subtitles(result) <- c("Protocol: xxxxx", paste("Analyte: ", unique(adpc_1$PARAM)), paste("Treatment:", unique(adpc_1$ACTARM)))
-main_footer(result) <- "NE: Not Estimable"
-
-result
-```
-
-## Table Implementing 1/3 Imputation Rule
-
-```{r variant2, test = list(result_v2 = "result")}
-lyt <- lyt_rows %>%
-  analyze_vars_in_cols(
-    vars = c("AVAL", "AVALCAT1", rep("AVAL", 8)),
-    .stats = c("n", "n_blq", "mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max"),
-    .formats = c(
-      n = "xx.", n_blq = "xx.", mean = format_sigfig(3), sd = format_sigfig(3), cv = "xx.x", median = format_sigfig(3),
-      geom_mean = format_sigfig(3), geom_cv = "xx.x", min = format_sigfig(3), max = format_sigfig(3)
-    ),
-    .labels = c(
-      n = "n", n_blq = "Number\nof\nLTRs/BLQs", mean = "Mean", sd = "SD", cv = "CV (%) Mean",
-      geom_mean = "Geometric Mean", geom_cv = "CV % Geometric Mean", median = "Median", min = "Minimum", max = "Maximum"
-    ),
-    imp_rule = "1/3",
-    .aligns = "decimal"
-  )
-
-result <- build_table(lyt, df = adpc_1, alt_counts_df = adsl) %>% prune_table()
-
-# Decorating
-main_title(result) <- "Summary of PK Concentrations by Nominal Time and Treatment: PK Evaluable"
-subtitles(result) <- c("Protocol: xxxxx", paste("Analyte: ", unique(adpc_1$PARAM)), paste("Treatment:", unique(adpc_1$ACTARM)))
-main_footer(result) <- c("NE: Not Estimable", "ND: Not Derived")
-
-result
-```
-
-## Table Implementing 1/2 Imputation Rule
-
-```{r variant3, test = list(result_v3 = "result")}
-lyt <- lyt_rows %>%
-  analyze_vars_in_cols(
-    vars = c("AVAL", "AVALCAT1", rep("AVAL", 8)),
-    .stats = c("n", "n_blq", "mean", "sd", "cv", "geom_mean", "geom_cv", "median", "min", "max"),
-    .formats = c(
-      n = "xx.", n_blq = "xx.", mean = format_sigfig(3), sd = format_sigfig(3), cv = "xx.x", median = format_sigfig(3),
-      geom_mean = format_sigfig(3), geom_cv = "xx.x", min = format_sigfig(3), max = format_sigfig(3)
-    ),
-    .labels = c(
-      n = "n", n_blq = "Number\nof\nLTRs/BLQs", mean = "Mean", sd = "SD", cv = "CV (%) Mean",
-      geom_mean = "Geometric Mean", geom_cv = "CV % Geometric Mean", median = "Median", min = "Minimum", max = "Maximum"
-    ),
-    imp_rule = "1/2",
-    .aligns = "decimal"
-  )
-
-result <- build_table(lyt, df = adpc_1, alt_counts_df = adsl) %>% prune_table()
-
-# Decorate table
-main_title(result) <- "Summary of PK Concentrations by Nominal Time and Treatment: PK Evaluable"
-subtitles(result) <- c("Protocol: xxxxx", paste("Analyte: ", unique(adpc_1$PARAM)), paste("Treatment:", unique(adpc_1$ACTARM)))
-main_footer(result) <- "ND: Not Derived"
-
-result
-```
-
-{{< include ../../test-utils/save_results.qmd >}}
-
 ## `teal` App
 
 ```{r teal, message=FALSE, opts.label='skip_if_testing'}