rtables (version 0.4.0)

select_all_levels: Add Combination Levels to split

Description

Add Combination Levels to split

Usage

select_all_levels
add_combo_levels(combosdf, trim = FALSE, first = FALSE, keep_levels = NULL)

Arguments

combosdf

data.frame/tbl_df. Columns valname, label, levelcombo, exargs. Of which levelcombo and exargs are list columns. Passing the select_all_levels object as a value in the comblevels column indicates that an overall/all-observations level should be created.

trim

logical(1). Should splits corresponding with 0 observations be kept when tabulating.

first

logical(1). Should the created split level be placed first in the levels (TRUE) or last (FALSE, the default).

keep_levels

character or NULL. If non-NULL, the levels to retain across both combination and individual levels.

Value

a closure suitable for use as a splitting function (splfun) when creating a table layout

Format

An object of class AllLevelsSentinel of length 0.

Examples

# NOT RUN {
library(tibble)
combodf <- tribble(
    ~valname, ~label, ~levelcombo, ~exargs,
    "A_B", "Arms A+B", c("A: Drug X", "B: Placebo"), list(),
    "A_C", "Arms A+C", c("A: Drug X", "C: Combination"), list())

l <- basic_table() %>%
    split_cols_by("ARM", split_fun = add_combo_levels(combodf)) %>%
    add_colcounts() %>%
    analyze("AGE")

build_table(l, DM)

la <- basic_table() %>%
    split_cols_by("ARM", split_fun = add_combo_levels(combodf, keep_levels = c("A_B", "A_C"))) %>%
    add_colcounts() %>%
    analyze("AGE")

build_table(la, DM)

smallerDM <- droplevels(subset(DM, SEX %in% c("M", "F") &
                        grepl("^(A|B)", ARM)))
l2 <- basic_table() %>%
    split_cols_by("ARM", split_fun = add_combo_levels(combodf[1,])) %>%
    split_cols_by("SEX", split_fun = add_overall_level("SEX_ALL", "All Genders")) %>%
    add_colcounts() %>%
    analyze("AGE")

l3 <-  basic_table() %>%
    split_cols_by("ARM", split_fun = add_combo_levels(combodf)) %>%
    add_colcounts() %>%
    split_rows_by("SEX", split_fun = add_overall_level("SEX_ALL", "All Genders")) %>%
    summarize_row_groups() %>%
    analyze("AGE")

build_table(l3, smallerDM)
# }