add_difference
Add difference between groups
Description
Add the difference between two groups (typically mean difference), along with the difference confidence interval and p-value.
Usage
add_difference( x, test = NULL, group = NULL, adj.vars = NULL, test.args = NULL, conf.level = 0.95, include = everything(), pvalue_fun = NULL, estimate_fun = NULL )
Arguments
x |
|
test |
List of formulas specifying statistical tests to perform for each variable,
e.g. |
group |
Column name (unquoted or quoted) of an ID or grouping variable.
The column can be used to calculate p-values with correlated data.
Default is |
adj.vars |
Variables to include in mean difference adjustment (e.g. in ANCOVA models) |
test.args |
List of formulas containing additional arguments to pass to
tests that accept arguments. For example, add an argument for all t-tests,
use |
conf.level |
Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval. |
include |
Variables to include in output. Input may be a vector of
quoted variable names, unquoted variable names, or tidyselect select helper
functions. Default is |
pvalue_fun |
Function to round and format p-values.
Default is style_pvalue.
The function must have a numeric vector input (the numeric, exact p-value),
and return a string that is the rounded/formatted p-value (e.g.
|
estimate_fun |
List of formulas specifying the formatting functions
to round and format differences. Default is
|
Example Output
Example 1
Example 2
Examples
# Example 1 ----------------------------------
add_difference_ex1 <-
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
add_difference_ex2 <-
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))