Merge tables

Merge gtsummary tables, e.g. tbl_regression, tbl_uvregression, tbl_stack, tbl_summary, tbl_svysummary, etc.

This function merges like tables. Generally, this means each of the tables being merged should have the same structure. When merging tables with different structures, rows may appear out of order. The ordering of rows can be updated with modify_table_body(~dplyr::arrange(.x, ...)).

Usage

tbl_merge(tbls, tab_spanner = NULL, merge_vars = NULL, tbl_ids = NULL)

Arguments

tbls

(list)
List of gtsummary objects to merge

tab_spanner

(character)
Character vector specifying the spanning headers. Must be the same length as tbls. The strings are interpreted with gt::md. Must be same length as tbls argument. Default is NULL, and places a default spanning header. If FALSE, no header will be placed.

merge_vars

(character)
Column names that are used as the merge IDs. The default is NULL, which merges on c(any_of(c("variable", "row_type", "var_label", "label"), cards::all_ard_groups()). Any column name included here that does not appear in all tables, will be removed.

tbl_ids

(character)
Optional character vector of IDs that will be assigned to the input tables. The ID is assigned by assigning a name to the tbls list, which is returned in x$tbls.

Value

A 'tbl_merge' object

Author

Daniel D. Sjoberg

Examples

# Example 1 ----------------------------------
# Side-by-side Regression Models
library(survival)

t1 <-
  glm(response ~ trt + grade + age, trial, family = binomial) %>%
  tbl_regression(exponentiate = TRUE)
t2 <-
  coxph(Surv(ttdeath, death) ~ trt + grade + age, trial) %>%
  tbl_regression(exponentiate = TRUE)

tbl_merge(
  tbls = list(t1, t2),
  tab_spanner = c("**Tumor Response**", "**Time to Death**")
)


  
Characteristic
      

        
Tumor Response
      
      

        
Time to Death
      
    
OR
      
95% CI
      
p-value
      
HR
      
95% CI
      
p-value
    
Chemotherapy Treatment











    Drug A
—
—


—
—

    Drug B
1.13
0.60, 2.13
0.7
1.30
0.88, 1.92
0.2
Grade











    I
—
—


—
—

    II
0.85
0.39, 1.85
0.7
1.21
0.73, 1.99
0.5
    III
1.01
0.47, 2.15
>0.9
1.79
1.12, 2.86
0.014
Age
1.02
1.00, 1.04
0.10
1.01
0.99, 1.02
0.3
Abbreviations: CI = Confidence Interval, HR = Hazard Ratio, OR = Odds Ratio
    

# Example 2 ----------------------------------
# Descriptive statistics alongside univariate regression, with no spanning header
t3 <-
  trial[c("age", "grade", "response")] %>%
  tbl_summary(missing = "no") %>%
  add_n() %>%
  modify_header(stat_0 ~ "**Summary Statistics**")
t4 <-
  tbl_uvregression(
    trial[c("ttdeath", "death", "age", "grade", "response")],
    method = coxph,
    y = Surv(ttdeath, death),
    exponentiate = TRUE,
    hide_n = TRUE
  )

tbl_merge(tbls = list(t3, t4)) %>%
  modify_spanning_header(everything() ~ NA_character_)


  
Characteristic
      
N
      
Summary Statistics1
      
HR
      
95% CI
      
p-value
    
Age
189
47 (38, 57)
1.01
0.99, 1.02
0.3
Grade
200







    I


68 (34%)
—
—

    II


68 (34%)
1.28
0.80, 2.05
0.3
    III


64 (32%)
1.69
1.07, 2.66
0.024
Tumor Response
193
61 (32%)
0.50
0.31, 0.78
0.003
Abbreviations: CI = Confidence Interval, HR = Hazard Ratio
    
1 Median (Q1, Q3); n (%)