Add the difference between two groups (typically mean difference), along with the difference confidence interval and p-value.

```
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
)
```

- x
`"tbl_summary"`

or`"tbl_svysummary"`

object- test
List of formulas specifying statistical tests to perform for each variable, e.g.

`list(all_continuous() ~ "t.test")`

. Common tests include`"t.test"`

or`"ancova"`

for continuous data, and`"prop.test"`

for dichotomous variables. See tests for details and more tests.- 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

`NULL`

. See tests for methods that utilize the`group=`

argument.- 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

`test.args = all_tests("t.test") ~ list(var.equal = TRUE)`

- 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

`everything()`

.- 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.

`pvalue_fun = function(x) style_pvalue(x, digits = 2)`

or equivalently,`purrr::partial(style_pvalue, digits = 2)`

).- estimate_fun
List of formulas specifying the formatting functions to round and format differences. Default is

`list(all_continuous() ~ style_sigfig, all_categorical() ~ function(x) paste0(style_sigfig(x * 100), "%"))`

Function to round and format difference. Default is`style_sigfig()`

Example 1

Example 2

Review list, formula, and selector syntax used throughout gtsummary

```
# 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))
```