Standard All vs Some (e.g. Related AEs) column structure

Usage

some_v_all_col_struct(
  lyt,
  colspan_trt_map = NULL,
  combo_map_df = NULL,
  trtvar = names(colspan_trt_map)[2],
  subgrp_var = NULL,
  subgrp_lbl = subgrp_var,
  all_lbl,
  subgrp_lvls,
  .pre = list(),
  .post = list()
)

Arguments

lyt: (PreDataTableLayouts). The layout to modify. This should virtually always be the object returned by basic_table.
colspan_trt_map: (data.frame). The spanning label map for the main columns, as given by create_colspan_map.
combo_map_df: (data.frame or NULL). A combination data frame as defined by add_combo_levels() with an additional is_control column indicating whether the virtual level will act as a reference (TRUE) or active (FALSE) group.
trtvar: (character(1) or NULL)
the treatment variable to split by. Defaults to the treatment variable in colspan_trt_map.
subgrp_var: (character(1) or NULL)
the name of the subgroup variable to split by within the trtvar split
subgrp_lbl: (character(1))
The label to put above the combination level representing subgrp_lvls
all_lbl: (character(1))
The label to put above the "All" column
subgrp_lvls: (characgter)
All level(s) to be included in the subgrp_lbl column.
.pre: (list of functions)
Passed to rtables::make_split_fun() as pre for treatment splitting.
.post: (list of functions)
Passed to rtables::make_split_fun() as post for treatment splitting after the standard column-structure processing.

Details

This column structure generating function is for comparing a single portion of the data (as represented by level(s) of subgrp_var) against the full data, comparison of AE counts to treatment-related AE counts being a motivating example.

Examples


 library(junco)
dat <- create_colspan_var(
  data.frame(
    TRT01A = factor(rep(c("Placebo", "Active 1", "Active 2"), each = 5)),
    GRADE = factor(rep(paste("Grade ", 1:5), 3))
  ),
  non_active_grp = "Placebo",
  non_active_grp_span_lbl = "Control",
  active_grp_span_lbl = "Active Treatment",
  colspan_var = "colspan_trt",
  trt_var = "TRT01A"
)
colspan_trt_map <- create_colspan_map(
  dat,
  non_active_grp = "Placebo",
  non_active_grp_span_lbl = "Control",
  active_grp_span_lbl = "Active Treatment",
  colspan_var = "colspan_trt",
  trt_var = "TRT01A"
)

lyt <- basic_table() |>
    some_v_all_col_struct(
    colspan_trt_map,
    subgrp_var = "GRADE",
    subgrp_lvls = c("Grade 4", "Grade 5"),
    subgrp_lbl = "High Grade",
    all_lbl = "All Grades")

build_table(lyt, dat)
#>                    Active Treatment                            Control        
#>           Active 1                  Active 2                   Placebo        
#>             (N=5)                     (N=5)                     (N=5)         
#>    All Grades   High Grade   All Grades   High Grade   All Grades   High Grade
#> ——————————————————————————————————————————————————————————————————————————————