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Count denom fraction statistic

Source: R/count_denom_fraction.R
response_by_var.Rd

Derives the count_denom_fraction statistic (i.e., 'xx /xx (xx.x percent)' ) Summarizes the number of unique subjects with a response = 'Y' for a given variable (e.g. TRTEMFL) within each category of another variable (e.g., SEX). Note that the denominator is derived using input df, in order to have these aligned with alt_source_df, it is expected that df includes all subjects.

Usage

response_by_var(
  df,
  labelstr = NULL,
  .var,
  .N_col,
  resp_var = NULL,
  id = "USUBJID",
  .format = jjcsformat_count_denom_fraction,
  ...
)

Arguments

df

Name of dataframe being analyzed.

labelstr

Custom label for the variable being analyzed.

.var

Name of the variable being analyzed. Records with non-missing values will be counted in the denominator.

.N_col

numeric(1). The total for the current column.

resp_var

Name of variable, for which, records with a value of 'Y' will be counted in the numerator.

id

Name of column in df which will have patient identifiers

.format

Format for the count/denominator/fraction output.

...

Additional arguments passed to the function.

Value

a RowsVerticalSection for use by the internal tabulation machinery of rtables

Details

This is an analysis function for use within analyze. Arguments df, .var will be populated automatically by rtables during the tabulation process.

Examples


library(dplyr)

ADAE <- data.frame(
  USUBJID = c(
    "XXXXX01", "XXXXX02", "XXXXX03", "XXXXX04", "XXXXX05",
    "XXXXX06", "XXXXX07", "XXXXX08", "XXXXX09", "XXXXX10"
  ),
  SEX_DECODE = c(
    "Female", "Female", "Male", "Female", "Male",
    "Female", "Male", "Female", "Male", "Female"
  ),
  TRT01A = c(
    "ARMA", "ARMB", "ARMA", "ARMB", "ARMB",
    "Placebo", "Placebo", "Placebo", "ARMA", "ARMB"
  ),
  TRTEMFL = c("Y", "Y", "N", "Y", "Y", "Y", "Y", "N", "Y", "Y")
)

ADAE <- ADAE |>
  mutate(
    TRT01A = as.factor(TRT01A),
    SEX_DECODE = as.factor(SEX_DECODE)
  )

lyt <- basic_table() |>
  split_cols_by("TRT01A") |>
  analyze(
    vars = "SEX_DECODE",
    var_labels = "Sex, n/Ns (%)",
    show_labels = "visible",
    afun = response_by_var,
    extra_args = list(resp_var = "TRTEMFL"),
    nested = FALSE
  )

result <- build_table(lyt, ADAE)

result
#>                     ARMA           ARMB         Placebo   
#> ——————————————————————————————————————————————————————————
#> Sex, n/Ns (%)                                             
#>   Female        1/1 (100.0%)   3/3 (100.0%)   1/2 (50.0%) 
#>   Male          1/2 (50.0%)    1/1 (100.0%)   1/1 (100.0%)