I am hoping to make a custom statistic column called Standardized Difference, which calculates the standardized mean difference for each categorical variable according to the formula: cat_smd=abs((p_1-p_0)/(sqrt(((p_1*(1-p_1)+p_0*(1-p_0))))/2)).
My challenge is that I don't know how to access/call/reference the proportions, but I know they have already been calculated in the tbl_summary. I think it involves {p}, but I don't know how to specify p_0 vs p_1. An example of some sample data and a table are below.
# create data
library(tidyverse)
library(gtsummary)
age = c(34, 26, 42, 39, 17, 32, 28, 35, 42, 42, 44, 21, 26, 19, 34, 38, 20, 23, 33, 39, 28, 30, 19, 30, 37, 22, 32, 26, 18, 26)
care = c(4, 2, 4, 4, 5, 4, 4, 4, 4, 4, 4, 2, 4, 4, 4, 4, 4, 4, 5, 4, 4, 4, 4, 4, 2, 2, 4, 4, 4, 4)
sex = c(1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1)
exp = c(1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0)
df = data.frame( age, sex, care, exp)
# create table summary
tbl = df %>%
tbl_summary(by=exp,
type = all_dichotomous() ~ "categorical") %>%
add_overall()
tbl
Desired statistic: cat_smd=abs((p_1-p_0)/(sqrt(((p_1*(1-p_1)+p_0*(1-p_0))))/2))
For example, for sex = 0, p_0 is 0.31, and p_1 is 0.50. The SMD would be 0.56.
Is anyone able to provide some advice about how to create this custom statistic?
I have answered this at: Add SMDs for each level of a categorical variable in gtsummary
To summarise, you can use my package
install.packages("devtools")
devtools::install_github("zheer-kejlberg/Z.gtsummary.addons")
library(Z.gtsummary.addons)
And add SMDs for each level of categorical variables using %>% add_SMD(location = "level") or to get SMDs for numeric and binary variables as well %>% add_SMD(location = "both")
For more examples, consult https://github.com/zheer-kejlberg/Z.gtsummary.addons