Convert gtsummary object to a huxtable object — as_hux

Function converts a gtsummary object to a huxtable object. A user can use this function if they wish to add customized formatting available via the huxtable functions. The huxtable package supports output to PDF via LaTeX, as well as HTML and Word.

as_hux_table(x, include = everything(), return_calls = FALSE)

as_hux_xlsx(x, file, include = everything(), bold_header_rows = TRUE)

Arguments

x: (gtsummary)
An object of class "gtsummary"
include: Commands to include in output. Input may be a vector of quoted or unquoted names. tidyselect and gtsummary select helper functions are also accepted. Default is everything().
return_calls: Logical. Default is FALSE. If TRUE, the calls are returned as a list of expressions.
file: File path for the output.
bold_header_rows: (scalar logical)
logical indicating whether to bold header rows. Default is TRUE

Value

A {huxtable} object

Excel Output

Use the as_hux_xlsx() function to save a copy of the table in an excel file. The file is saved using huxtable::quick_xlsx().

Author

David Hugh-Jones, Daniel D. Sjoberg

Examples

trial |>
  tbl_summary(by = trt, include = c(age, grade)) |>
  add_p() |>
  as_hux_table()
#>             Characteristic   Drug AN = 98   Drug BN = 102   p-value  
#>           ───────────────────────────────────────────────────────────
#>             Age              46 (37, 60)     48 (39, 56)      0.7    
#>             Unknown               7               4                  
#>             Grade                                             0.9    
#>             I                  35 (36%)       33 (32%)               
#>             II                 32 (33%)       36 (35%)               
#>             III                31 (32%)       33 (32%)               
#>           ───────────────────────────────────────────────────────────
#>             Median (Q1, Q3); n (%)                                   
#>             Wilcoxon rank sum test; Pearson's Chi-squared            
#>             test                                                     
#> 
#> Column names: label, stat_1, stat_2, p.value