Add differences between groups

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()


  
Characteristic
      
N
      
Drug A

N = 981
      
Drug B

N = 1021
      
Difference2
      
95% CI2
      
p-value2
    
Age
189
47 (15)
47 (14)
-0.44
-4.6, 3.7
0.8
Marker Level (ng/mL)
190
1.02 (0.89)
0.82 (0.83)
0.20
-0.05, 0.44
0.12
Tumor Response
193
29%
34%
-4.2%
-18%, 9.9%
0.6
Patient Died
200
53%
59%
-5.8%
-21%, 9.0%
0.5
Abbreviation: CI = Confidence Interval
    
1 Mean (SD); %
    
2 Welch Two Sample t-test; 2-sample test for equality of proportions with continuity correction
    

# 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))


  
Characteristic
      
N
      
Drug A

N = 981
      
Drug B

N = 1021
      
Adjusted Difference2
      
95% CI2
      
p-value2
    
Age
189
47 (15)
47 (14)
-0.36
-4.5, 3.8
0.9
Marker Level (ng/mL)
190
1.02 (0.89)
0.82 (0.83)
0.19
-0.05, 0.43
0.12
Abbreviation: CI = Confidence Interval
    
1 Mean (SD)
    
2 ANCOVA