add_difference.tbl_summary: Add differences between groups

In gtsummary: Presentation-Ready Data Summary and Analytic Result Tables

Add differences between groups

Description

Adds difference to tables created by tbl_summary(). The difference between two groups (typically mean or rate difference) is added to the table along with the difference's confidence interval and a p-value (when applicable).

Usage

## S3 method for class 'tbl_summary'
add_difference(
  x,
  test = NULL,
  group = NULL,
  adj.vars = NULL,
  test.args = NULL,
  conf.level = 0.95,
  include = everything(),
  pvalue_fun = label_style_pvalue(digits = 1),
  estimate_fun = list(c(all_continuous(), all_categorical(FALSE)) ~ label_style_sigfig(),
    all_dichotomous() ~ label_style_sigfig(scale = 100, suffix = "%"), all_tests("smd")
    ~ label_style_sigfig()),
  ...
)

Arguments

x	(tbl_summary) table created with tbl_summary()
test	(formula-list-selector) Specifies the tests/methods to perform for each variable, e.g. list(all_continuous() ~ "t.test", all_dichotomous() ~ "prop.test", all_categorical(FALSE) ~ "smd"). See below for details on default tests and ?tests for details on available tests and creating custom tests.
group	(tidy-select) Variable name of an ID or grouping variable. The column can be used to calculate p-values with correlated data. Default is NULL. See tests for methods that utilize the group argument.
adj.vars	(tidy-select) Variables to include in adjusted calculations (e.g. in ANCOVA models). Default is NULL.
test.args	(formula-list-selector) Containing additional arguments to pass to tests that accept arguments. For example, add an argument for all t-tests, use test.args = all_tests("t.test") ~ list(var.equal = TRUE).
conf.level	(numeric) a scalar in the interval ⁠(0, 1)⁠ indicating the confidence level. Default is 0.95
include	(tidy-select) Variables to include in output. Default is everything().
pvalue_fun	(function) Function to round and format p-values. Default is label_style_pvalue(). The function must have a numeric vector input, and return a string that is the rounded/formatted p-value (e.g. pvalue_fun = label_style_pvalue(digits = 2)).
estimate_fun	(formula-list-selector) List of formulas specifying the functions to round and format differences and confidence limits.
...	These dots are for future extensions and must be empty.

Value

a gtsummary table of class "tbl_summary"

Examples

# Example 1 ----------------------------------
trial |>
  select(trt, age, marker, response, death) %>%
  tbl_summary(
    by = trt,
    statistic =
      list(
        all_continuous() ~ "{mean} ({sd})",
        all_dichotomous() ~ "{p}%"
      ),
    missing = "no"
  ) |>
  add_n() |>
  add_difference()

# Example 2 ----------------------------------
# ANCOVA adjusted for grade and stage
trial |>
  select(trt, age, marker, grade, stage) %>%
  tbl_summary(
    by = trt,
    statistic = list(all_continuous() ~ "{mean} ({sd})"),
    missing = "no",
    include = c(age, marker, trt)
  ) |>
  add_n() |>
  add_difference(adj.vars = c(grade, stage))

gtsummary documentation built on Oct. 5, 2024, 1:06 a.m.