tests/testthat/test-independent-testing-n_subject.R

In Merck/metalite.ae: Adverse Events Analysis Using 'metalite'

r2rtf_adae <- r2rtf::r2rtf_adae

test_that("if group = ... is not a factor, throw errors", {
  expect_error(n_subject(r2rtf_adae$USUBJID, as.character(r2rtf_adae$TRTA)))
})

test_that("if par = NULL, return the number of subjects in each group (take the r2rtf::r2rtf_adae dataset as an example)", {
  r2rtf_adae$TRTA <- factor(r2rtf_adae$TRTA)

  count <- r2rtf_adae |>
    dplyr::group_by(TRTA) |>
    dplyr::summarise(n = dplyr::n_distinct(USUBJID)) |>
    tidyr::pivot_wider(names_from = "TRTA", values_from = "n", names_sep = " ") |>
    data.frame()

  n_sub <- n_subject(r2rtf_adae$USUBJID, r2rtf_adae$TRTA)
  names(count) <- c("Placebo", "Xanomeline High Dose", "Xanomeline Low Dose")
  expect_equal(n_sub, count)
})

test_that("if, say, par = AEDECOD, return the number of subject per group per AE (take the r2rtf::r2rtf_adae dataset as an example)", {
  r2rtf_adae$TRTA <- factor(r2rtf_adae$TRTA)

  count <- r2rtf_adae |>
    dplyr::group_by(TRTA, AEDECOD) |>
    dplyr::summarise(n = dplyr::n_distinct(USUBJID)) |>
    tidyr::pivot_wider(names_from = "TRTA", values_from = "n", names_sep = " ") |>
    data.frame() |>
    dplyr::arrange(AEDECOD)

  count[is.na(count)] <- 0


  n_sub <- n_subject(r2rtf_adae$USUBJID, r2rtf_adae$TRTA, r2rtf_adae$AEDECOD)
  names(count) <- c("name", "Placebo", "Xanomeline High Dose", "Xanomeline Low Dose")
  attr(count$name, "label") <- NULL
  expect_equal(n_sub, count)
})