Add SMDs for each level of a categorical variable in gtsummary

I would like to create a table one of baseline characteristics, stratified by an exposure, that shows SMDs between the exposure groups for every level of the categorical variables. Currently, adding SMDs via add_difference only gives an overall SMD for the variable as shown with Grade below.

library(gtsummary)
#> Warning: package 'gtsummary' was built under R version 4.2.3

tbl <- 
  trial %>%
  select(trt, age, response, grade) %>%
  tbl_summary(by = trt, missing = "no") %>%
  add_difference(everything() ~ "smd")

tbl

table

I cannot figure out how to make them as a custom function within gtsummary. Alternatively, bal.tab() from the cobalt package calculates them by level, but I also can't figure out how to add them to my tbl_summary from that package.

I appreciate any help!

UPDATE: The function is now incorporated into a package, which can be loaded with:

install.packages("devtools")
devtools::install_github("zheer-kejlberg/Z.gtsummary.addons")
library(Z.gtsummary.addons)

I've written some code to do just this with gtsummary tables at https://github.com/zheer-kejlberg/gtsummary-SMDs.

Use %>% add_SMD(location = "level") to add SMDs to each level of all categorical variables or %>% add_SMD(location = "both") to get both the "overall SMDs" (Mahalanobis distances) and the per-level SMDs.

Behind the scenes, the function uses dummy coding for the per-level SMDs.

There's not as yet support for confidence intervals on SMDs, but that's in the pipeline. See the output here:

EDIT (Nov 12 2023): The function has now been updated with support for confidence intervals (the ci argument) and custom number of decimals (the decimals argument).