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Merge Multiple gtsummary Tables (Descriptive, Univariate, Multivariable)

Source: R/merge_tables.R
merge_tables.Rd

Flexibly merges any 2 or more `gtsummary` tables (e.g., from `descriptive_table()`, `uni_reg()`, `multi_reg()`) into a single table using `tbl_merge()`. Automatically applies column spanners based on the order of inputs.

Usage

merge_tables(..., spanners = NULL)

Arguments

...

Two or more `gtsummary` table objects to merge.

spanners

Optional character vector of column header titles. If not supplied, defaults to `"Table 1"`, `"Univariate"`, `"Multivariable"` etc.

Value

A merged `gtsummary::tbl_merge` object.

Examples

# \donttest{
if (requireNamespace("mlbench", quietly = TRUE)) {
  data("PimaIndiansDiabetes2", package = "mlbench")
  library(dplyr)
  library(gtregression)

  # Prepare data
  pima <- PimaIndiansDiabetes2 |>
    mutate(
      diabetes = ifelse(diabetes == "pos", 1, 0),
      bmi_cat = cut(
        mass,
        breaks = c(-Inf, 18.5, 24.9, 29.9, Inf),
        labels = c("Underweight", "Normal", "Overweight", "Obese")
      )
    )

  # Descriptive table
  desc_tbl <- descriptive_table(pima,
                                exposures = c("age", "bmi_cat"),
                                by = "diabetes")

  # Univariate logistic regression
  uni_tbl <- uni_reg(
    data = pima,
    outcome = "diabetes",
    exposures = c("age", "bmi_cat"),
    approach = "logit"
  )

  # Multivariable logistic regression
  multi_tbl <- multi_reg(
    data = pima,
    outcome = "diabetes",
    exposures = c("age", "bmi_cat"),
    approach = "logit"
  )

  # Merge descriptive + univariate + multivariate
  merge_tables(desc_tbl, uni_tbl, multi_tbl)

  # Merge with custom spanners
  merge_tables(desc_tbl, uni_tbl, spanners = c("Summary", "Crude"))

  # Merge just uni and multi
  merge_tables(uni_tbl, multi_tbl)
}
#> Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
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Characteristic
      
        
Table 1

      		
      
        
Table 2

      		
    
N
      OR
      95% CI
      p-value
      Adjusted OR
      95% CI
      p-value
    
age
768
1.04
1.03, 1.06
<0.001
1.05
1.03, 1.06
<0.001
bmi_cat
757











    Underweight


—
—


—
—

    Normal


156,076
0.00, 

>0.9
92,942
0.00, 

>0.9
    Overweight


609,548
0.00, 

>0.9
380,559
0.00, 

>0.9
    Obese


1,833,523
0.00, 

>0.9
1,189,166
0.00, 

>0.9
Abbreviations: CI = Confidence Interval, OR = Odds Ratio
    
N = 757 complete observations included in the multivariate model
    
# }