split_rows_by: Add Rows according to levels of a variable

In rtables: Reporting Tables

Add Rows according to levels of a variable

Description

Add Rows according to levels of a variable

Usage

split_rows_by(
  lyt,
  var,
  labels_var = var,
  split_label = var,
  split_fun = NULL,
  format = NULL,
  na_str = NA_character_,
  nested = TRUE,
  child_labels = c("default", "visible", "hidden"),
  label_pos = "hidden",
  indent_mod = 0L,
  page_by = FALSE,
  page_prefix = split_label,
  section_div = NA_character_
)

Arguments

lyt	layout object pre-data used for tabulation
var	string, variable name
labels_var	string, name of variable containing labels to be displayed for the values of var
split_label	string. Label string to be associated with the table generated by the split. Not to be confused with labels assigned to each child (which are based on the data and type of split during tabulation).
split_fun	function/NULL. custom splitting function See custom_split_funs
format	FormatSpec. Format associated with this split. Formats can be declared via strings ("xx.x") or function. In cases such as analyze calls, they can character vectors or lists of functions.
na_str	character(1). String that should be displayed when the value of x is missing. Defaults to "NA".
nested	boolean. Should this layout instruction be applied within the existing layout structure if possible (TRUE, the default) or as a new top-level element ('FALSE). Ignored if it would nest a split underneath analyses, which is not allowed.
child_labels	string. One of "default", "visible", "hidden". What should the display behavior be for the labels (i.e. label rows) of the children of this split. Defaults to "default" which flags the label row as visible only if the child has 0 content rows.
label_pos	character(1). Location the variable label should be displayed, Accepts "hidden" (default for non-analyze row splits), "visible", "topleft", and - for analyze splits only - "default". For analyze calls, "default" indicates that the variable should be visible if and only if multiple variables are analyzed at the same level of nesting.
indent_mod	numeric. Modifier for the default indent position for the structure created by this function(subtable, content table, or row) and all of that structure's children. Defaults to 0, which corresponds to the unmodified default behavior.
page_by	logical(1). Should pagination be forced between different children resulting form this split. An error will rise if the selected split does not contain at least one value that is not NA.
page_prefix	character(1). Prefix, to be appended with the split value, when forcing pagination between the children of this split/table
section_div	character(1). String which should be repeated as a section divider after each group defined by this split instruction, or NA_character_ (the default) for no section divider.

Value

A PreDataTableLayouts object suitable for passing to further layouting functions, and to build_table.

Custom Splitting Function Details

User-defined custom split functions can perform any type of computation on the incoming data provided that they meet the contract for generating 'splits' of the incoming data 'based on' the split object.

Split functions are functions that accept:

df

data.frame of incoming data to be split

spl

a Split object. this is largely an internal detail custom functions will not need to worry about, but obj_name(spl), for example, will give the name of the split as it will appear in paths in the resulting table

vals

Any pre-calculated values. If given non-null values, the values returned should match these. Should be NULL in most cases and can likely be ignored

labels

Any pre-calculated value labels. Same as above for values

trim

If TRUE, resulting splits that are empty should be removed

(Optional) .spl_context

a data.frame describing previously performed splits which collectively arrived at df

The function must then output a named list with the following elements:

values

The vector of all values corresponding to the splits of df

datasplit

a list of data.frames representing the groupings of the actual observations from df.

labels

a character vector giving a string label for each value listed in the values element above

(Optional) extras

If present, extra arguments are to be passed to summary and analysis functions whenever they are executed on the corresponding element of datasplit or a subset thereof

One way to generate custom splitting functions is to wrap existing split functions and modify either the incoming data before they are called or their outputs.

Note

If var is a factor with empty unobserved levels and labels_var is specified, it must also be a factor with the same number of levels as var. Currently the error that occurs when this is not the case is not very informative, but that will change in the future.

Author(s)

Gabriel Becker

Examples

lyt <- basic_table() %>%
    split_cols_by("ARM") %>%
    split_rows_by("RACE", split_fun = drop_split_levels) %>%
    analyze("AGE", mean, var_labels = "Age", format = "xx.xx")

tbl <- build_table(lyt, DM)
tbl

lyt2 <- basic_table() %>%
    split_cols_by("ARM") %>%
    split_rows_by("RACE") %>%
    analyze("AGE", mean, var_labels = "Age", format = "xx.xx")

tbl2 <- build_table(lyt2, DM)
tbl2

lyt3 <- basic_table() %>%
    split_cols_by("ARM") %>%
    split_cols_by("SEX") %>%
    summarize_row_groups(label_fstr = "Overall (N)") %>%
    split_rows_by("RACE", split_label = "Ethnicity", labels_var = "ethn_lab",
                  split_fun = drop_split_levels) %>%
    summarize_row_groups("RACE", label_fstr = "%s (n)") %>%
    analyze("AGE", var_labels = "Age", afun = mean, format = "xx.xx")

lyt3

library(dplyr)
DM2 <- DM %>%
    filter(SEX %in% c("M", "F")) %>%
    mutate(
        SEX = droplevels(SEX),
        gender_lab = c("F" = "Female", "M" = "Male",
                       "U" = "Unknown",
                       "UNDIFFERENTIATED" = "Undifferentiated")[SEX],
        ethn_lab = c(
            "ASIAN" = "Asian",
            "BLACK OR AFRICAN AMERICAN" = "Black or African American",
            "WHITE" = "White",
            "AMERICAN INDIAN OR ALASKA NATIVE" = "American Indian or Alaska Native",
             "MULTIPLE" = "Multiple",
             "NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER" =
                 "Native Hawaiian or Other Pacific Islander",
             "OTHER" = "Other", "UNKNOWN" = "Unknown"
        )[RACE]
    )

tbl3 <- build_table(lyt3, DM2)
tbl3

rtables documentation built on Aug. 30, 2023, 5:07 p.m.