gtsummary R package: pre-post summary table with paired 2-sample tests? - r

Question

Is it possible to use the gtsummary R package to make a pre-post summary table with 2 columns that summarize multiple variables at 2 different time points?
I know the arsenal R package supports this, but I would prefer to use gtsummary if possible since it supports the tidyverse.
For example, is it possible to make a pre-post summary table using gtsummary that is similar to the table in this example? Here is a simpler version of the dataset from their example:
dat <- data.frame(
tp = paste0("Time Point ", c(1, 2, 1, 2, 1, 2, 1, 2, 1, 2)),
id = c(1, 1, 2, 2, 3, 3, 4, 4, 5, 6),
Cat = c("A", "A", "A", "B", "B", "B", "B", "A", NA, "B"),
Fac = factor(c("A", "B", "C", "A", "B", "C", "A", "B", "C", "A")),
Num = c(1, 2, 3, 4, 4, 3, 3, 4, 0, NA),
stringsAsFactors = FALSE)
Note the dataset is in "long format": tp is the 2 pre-post time points, and id is the subject ID for the 2 repeated measures. To make the table, Cat and Fac are categorical variables that would be summarized as count(%) at each time point, and use McNemar's test to compare if they change over time. Num is a numeric variable that would be summarized as mean(standard deviation) at each time point, and use paired t-test to assess change over time.

Answer 1

Yes, as of gtsummary v1.3.6, there is a function called add_difference() for this express purpose. The function supports both paired (e.g. pre- and post-responses), and unpaired data. The method is specified in the test= argument.
Worked example here: http://www.danieldsjoberg.com/gtsummary/articles/gallery.html#paired-test
Here's an unpaired example:
trial %>%
select(trt, age, marker, response, death) %>%
tbl_summary(
by = trt,
statistic =
list(
all_continuous() ~ "{mean} ({sd})",
all_dichotomous() ~ "{p}%"
),
missing = "no"
) %>%
add_n() %>%
add_difference()