summarize_colvars: Summarize variables in columns

In tern: Create Common TLGs Used in Clinical Trials

Summarize variables in columns

Description

The analyze function summarize_colvars() uses the statistics function s_summary() to analyze variables that are arranged in columns. The variables to analyze should be specified in the table layout via column splits (see rtables::split_cols_by() and rtables::split_cols_by_multivar()) prior to using summarize_colvars().

The function is a minimal wrapper for rtables::analyze_colvars(), a function typically used to apply different analysis methods in rows for each column variable. To use the analysis methods as column labels, please refer to the analyze_vars_in_cols() function.

Usage

summarize_colvars(
  lyt,
  na_str = default_na_str(),
  ...,
  .stats = c("n", "mean_sd", "median", "range", "count_fraction"),
  .stat_names = NULL,
  .formats = NULL,
  .labels = NULL,
  .indent_mods = NULL
)

Arguments

lyt	(PreDataTableLayouts) layout that analyses will be added to.
na_str	(string) string used to replace all NA or empty values in the output.
...	arguments passed to s_summary().
.stats	(character) statistics to select for the table.
.stat_names	(character) names of the statistics that are passed directly to name single statistics (.stats). This option is visible when producing rtables::as_result_df() with make_ard = TRUE.
.formats	(named character or list) formats for the statistics. See Details in analyze_vars for more information on the "auto" setting.
.labels	(named character) labels for the statistics (without indent).
.indent_mods	(named vector of integer) indent modifiers for the labels. Each element of the vector should be a name-value pair with name corresponding to a statistic specified in .stats and value the indentation for that statistic's row label.

Value

A layout object suitable for passing to further layouting functions, or to rtables::build_table(). Adding this function to an rtable layout will summarize the given variables, arrange the output in columns, and add it to the table layout.

See Also

rtables::split_cols_by_multivar() and analyze_colvars_functions.

Examples

dta_test <- data.frame(
  USUBJID = rep(1:6, each = 3),
  PARAMCD = rep("lab", 6 * 3),
  AVISIT = rep(paste0("V", 1:3), 6),
  ARM = rep(LETTERS[1:3], rep(6, 3)),
  AVAL = c(9:1, rep(NA, 9)),
  CHG = c(1:9, rep(NA, 9))
)

## Default output within a `rtables` pipeline.
basic_table() %>%
  split_cols_by("ARM") %>%
  split_rows_by("AVISIT") %>%
  split_cols_by_multivar(vars = c("AVAL", "CHG")) %>%
  summarize_colvars() %>%
  build_table(dta_test)

## Selection of statistics, formats and labels also work.
basic_table() %>%
  split_cols_by("ARM") %>%
  split_rows_by("AVISIT") %>%
  split_cols_by_multivar(vars = c("AVAL", "CHG")) %>%
  summarize_colvars(
    .stats = c("n", "mean_sd"),
    .formats = c("mean_sd" = "xx.x, xx.x"),
    .labels = c(n = "n", mean_sd = "Mean, SD")
  ) %>%
  build_table(dta_test)

## Use arguments interpreted by `s_summary`.
basic_table() %>%
  split_cols_by("ARM") %>%
  split_rows_by("AVISIT") %>%
  split_cols_by_multivar(vars = c("AVAL", "CHG")) %>%
  summarize_colvars(na.rm = FALSE) %>%
  build_table(dta_test)

tern documentation built on April 15, 2025, 1:31 a.m.