Stratified gtsummary tables

Build a stratified gtsummary table. Any gtsummary table that accepts a data frame as its first argument can be stratified.

• In tbl_strata(), the stratified or subset data frame is passed to the function in .tbl_fun=, e.g. purrr::map(data, .tbl_fun).

• In tbl_strata2(), both the stratified data frame and the strata level are passed to .tbl_fun=, e.g. purrr::map2(data, strata, .tbl_fun).

When merging, keep in mind that merging works best with like tables. See tbl_merge() for details.

tbl_strata(
  data,
  strata,
  .tbl_fun,
  ...,
  .sep = ", ",
  .combine_with = c("tbl_merge", "tbl_stack"),
  .combine_args = NULL,
  .header = ifelse(.combine_with == "tbl_merge", "**{strata}**", "{strata}"),
  .quiet = NULL
)

tbl_strata2(
  data,
  strata,
  .tbl_fun,
  ...,
  .sep = ", ",
  .combine_with = c("tbl_merge", "tbl_stack"),
  .combine_args = NULL,
  .header = ifelse(.combine_with == "tbl_merge", "**{strata}**", "{strata}"),
  .quiet = TRUE
)

Arguments

data

(data.frame, survey.design)
a data frame or survey object

strata

(tidy-select)
character vector or tidy-selector of columns in data to stratify results by. Only observed combinations are shown in results.

.tbl_fun

(function) A function or formula. If a function, it is used as is. If a formula, e.g. ~ .x %>% tbl_summary() %>% add_p(), it is converted to a function. The stratified data frame is passed to this function.

...

Additional arguments passed on to the .tbl_fun function.

.sep

(string)
when more than one stratifying variable is passed, this string is used to separate the levels in the spanning header. Default is ", "

.combine_with

(string)
One of c("tbl_merge", "tbl_stack"). Names the function used to combine the stratified tables.

.combine_args

(named list)
named list of arguments that are passed to function specified in .combine_with

.header

(string)
String indicating the headers that will be placed. Default is "**{strata}**" when .combine_with = "tbl_merge" and "{strata}" when .combine_with = "tbl_stack". Items placed in curly brackets will be evaluated according to glue::glue() syntax. - strata stratum levels - n N within stratum - N Overall N

The evaluated value of .header is also available within tbl_strata2(.tbl_fun)

.quiet

Tips

• tbl_summary()

  • The number of digits continuous variables are rounded to is determined separately within each stratum of the data frame. Set the digits= argument to ensure continuous variables are rounded to the same number of decimal places.

  • If some levels of a categorical variable are unobserved within a stratum, convert the variable to a factor to ensure all levels appear in each stratum's summary table.

  • The summary type for variables (e.g. continuous vs categorical vs dichotomous) are determined separately within stratum. Use the tbl_summary(type) argument to assign a summary type consistent across all tables being combined.

  • By default, a "missing" row appears when there are missing values only. Use the tbl_summary(missing) argument to ensure there is always/never a missing row for the combining of the tables.

Author

Daniel D. Sjoberg

Examples

# Example 1 ----------------------------------
trial |>
  select(age, grade, stage, trt) |>
  mutate(grade = paste("Grade", grade)) |>
  tbl_strata(
    strata = grade,
    .tbl_fun =
      ~ .x |>
        tbl_summary(by = trt, missing = "no") |>
        add_n(),
    .header = "**{strata}**, N = {n}"
  )


  
Characteristic
      

        
Grade I, N = 68
      
      

        
Grade II, N = 68
      
      

        
Grade III, N = 64
      
    
N
      
Drug A

N = 351
      
Drug B

N = 331
      
N
      
Drug A

N = 321
      
Drug B

N = 361
      
N
      
Drug A

N = 311
      
Drug B

N = 331
    
Age
66
46 (36, 60)
48 (42, 55)
62
45 (31, 55)
51 (42, 58)
61
52 (42, 61)
45 (36, 52)
T Stage
68




68




64



    T1


8 (23%)
9 (27%)


14 (44%)
9 (25%)


6 (19%)
7 (21%)
    T2


8 (23%)
10 (30%)


8 (25%)
9 (25%)


9 (29%)
10 (30%)
    T3


11 (31%)
7 (21%)


5 (16%)
6 (17%)


6 (19%)
8 (24%)
    T4


8 (23%)
7 (21%)


5 (16%)
12 (33%)


10 (32%)
8 (24%)
1 Median (Q1, Q3); n (%)
    

# Example 2 ----------------------------------
trial |>
  select(grade, response) |>
  mutate(grade = paste("Grade", grade)) |>
  tbl_strata2(
    strata = grade,
    .tbl_fun =
      ~ .x %>%
        tbl_summary(
          label = list(response = .y),
          missing = "no",
          statistic = response ~ "{p}%"
        ) |>
        add_ci(pattern = "{stat} ({ci})") |>
        modify_header(stat_0 = "**Rate (95% CI)**") |>
        remove_footnote_header(stat_0),
    .combine_with = "tbl_stack",
    .combine_args = list(group_header = NULL)
  ) |>
  modify_caption("**Response Rate by Grade**")


  
Response Rate by Grade

  
Characteristic
      
Rate (95% CI)
    
Grade I
31% (21%, 44%)
Grade II
30% (20%, 43%)
Grade III
33% (22%, 46%)
Abbreviation: CI = Confidence Interval