Update metalite_table1.R

[Emilylyu99]

Handling missing value when group contain missing values

The code is following:
install.packages("metalite.table1")
library(metalite.table1)
metalite_table1(~ AGE + SEX + RACE + BMIBLGR1 | ARM, data = r2rtf::r2rtf_adsl, id = "USUBJID")
library(dplyr)

handle_missing_group <- function(data, group, missing_group) {
if (missing_group == "ignore") {
data <- data[!is.na(data[[group]]), ]
message("Ignore missing values in the group variable.")
} else if (missing_group == "count") {
data[[group]] <- addNA(data[[group]], ifany = TRUE)
levels(data[[group]]) <- c(levels(data[[group]]), "Missing")
} else if (missing_group == "display") {
data[[group]] <- addNA(data[[group]], ifany = TRUE)
levels(data[[group]]) <- c(levels(data[[group]]), "Missing")
} else {
stop("Invalid value for 'missing_group'.")
}

return(data)
}
data <- r2rtf::r2rtf_adsl

updated_data <- data %>%
mutate(
AGE = if_else(runif(n()) < 0.1, NA, AGE),
SEX = if_else(runif(n()) < 0.04, NA, SEX),
RACE = if_else(runif(n()) < 0.07, NA, RACE),
BMIBLGR1 = if_else(runif(n()) < 0.02, NA, BMIBLGR1)
)
updated_data <- handle_missing_group(updated_data, "AGE", "count")

metalite_table1(~ AGE + SEX + RACE + BMIBLGR1 | ARM, data = updated_data, id = "USUBJID")

we can change the "updated_data <- handle_missing_group(updated_data, "AGE", "count")" to "updated_data <- handle_missing_group(updated_data, "AGE", "display")" or "updated_data <- handle_missing_group(updated_data, "AGE", "ignore")".

when we fill "updated_data <- handle_missing_group(updated_data, "AGE":