Add frequency and % of missing values in gtsummary - gtsummary

Question

df_nhpi %>%
select(AGE, SEX, MAR_STAT, HEIGHT, WEIGHT, BMI, HTN, HTNMED, MI, Smoking, COPD, CANCER, DIABETES) %>%
tbl_summary(by = SEX,
label = list(MAR_STAT ~ 'Marital Status',
HTN ~ 'Hypertension',
HTNMED ~ 'Hypertension Medication',
MI ~ 'Heart Attack',
Smoking ~ 'Smoking Status',
COPD ~ 'Chronic Obstructive Pulmonary Disease'),
type = list(c("HTN","HTNMED", "MI", "COPD", "CANCER") ~ "categorical"),
missing = "ifany",
missing_text = "Unknown",
statistic = list(all_continuous() ~ "{mean} ({sd})",
all_categorical() ~ "{n} ({p}%)"),
digits = all_continuous() ~ 2, percent = "column") %>%
add_stat_label() %>%
add_p(test = all_continuous() ~ "t.test", pvalue_fun =
function(x) style_pvalue(x, digits = 3)) %>%
bold_p() %>%
modify_caption("**Table 1. Baseline Characteristics**") %>% bold_labels()
I'm trying to generate a table one. But, the issue here is, I want % for missing values across columns (specifically for categorical variables) and at the same time, I don't want missing values to be included while calculating p-values. I'm trying to do this in single chunk of code. Is there anyway to do this or should I go for the conventional method?
I've been searching the whole internet for the past three days. But, I don't find anything that works in my case.
PS: mutate and forcats doesn't work as it skews my p-values.

Answer 1

I prepared two solutions that both report the proportion of missing data. Hopefully one of them works for you!
library(gtsummary)
packageVersion("gtsummary")
#> [1] '1.5.2'
# add % missing in new column
tbl1 <-
trial %>%
tbl_summary(
by = trt,
include = response,
type = all_dichotomous() ~ "categorical",
missing = "no"
) %>%
add_p() %>%
add_n(statistic = "{n_miss} ({p_miss}%)") %>%
modify_header(n = "**Missing**")
# prepare tbl_summary with rows for missing, then merge in p-values
tbl2 <-
trial %>%
dplyr::mutate(response = forcats::fct_explicit_na(factor(response))) %>%
tbl_summary(
by = trt,
include = response,
label = list(response = "Tumor Response")
) %>%
list(tbl1 %>% modify_column_hide(c(n, all_stat_cols()))) %>%
tbl_merge(tab_spanner = FALSE)
Created on 2022-03-22 by the reprex package (v2.0.1)