Merge tables

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

Usage

tbl_merge(tbls, tab_spanner = 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.

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
      
    
OR1
      
95% CI1
      
p-value
      
HR1
      
95% CI1
      
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
1 OR = Odds Ratio, CI = Confidence Interval, HR = Hazard 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
      
HR2
      
95% CI2
      
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
1 Median (Q1, Q3); n (%)
    
2 HR = Hazard Ratio, CI = Confidence Interval