## ----include=FALSE------------------------------------------------------------
knitr::opts_chunk$set(
  comment = "#>",
  collapse = TRUE,
  out.width = "100%",
  dpi = 150
)

## -----------------------------------------------------------------------------
library(metalite.ae)

## -----------------------------------------------------------------------------
adsl <- forestly::forestly_adsl
adae <- forestly::forestly_adae

adsl$TRT01A <- factor(
  adsl$TRT01A,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)
adae$TRTA <- factor(
  adae$TRTA,
  levels = c("Xanomeline Low Dose", "Placebo"),
  labels = c("Low Dose", "Placebo")
)

analysis_plan <- metalite::plan(
  analysis = "ae_specific",
  population = "apat",
  observation = "wk12",
  parameter = "rel"
)

meta <- metalite::meta_adam(observation = adae, population = adsl) |>
  metalite::define_plan(analysis_plan) |>
  metalite::define_population(
    name = "apat",
    var = c(
      "USUBJID", "SAFFL", "TRT01A", "TRTDUR",
      "SITEID", "SEX", "RACE", "AGE"
    ),
    group = "TRT01A",
    subset = SAFFL == "Y",
    label = "All Participants as Treated"
  ) |>
  metalite::define_observation(
    name = "wk12",
    var = c(
      "USUBJID", "SAFFL", "TRTA", "AEDECOD", "AEBODSYS", "AEREL",
      "AESER", "AEOUT", "AEACN", "AESDTH", "ASTDT", "AENDT"
    ),
    group = "TRTA",
    subset = SAFFL == "Y",
    label = "Weeks 0 to 12"
  ) |>
  metalite::define_parameter(
    name = "rel",
    term1 = "Drug-Related",
    term2 = "",
    subset = AEREL %in% c("POSSIBLE", "PROBABLE"),
    var = "AEDECOD",
    soc = "AEBODSYS",
    label = "Drug-related AEs"
  ) |>
  metalite::define_analysis(
    name = "ae_specific",
    title = "Participants with Drug-Related Adverse Events"
  ) |>
  metalite::meta_build()

## -----------------------------------------------------------------------------
rtf_dir <- if (dir.exists("vignettes/rtf")) "vignettes/rtf" else "rtf"

prepare_ae_specific(
  meta,
  population = "apat",
  observation = "wk12",
  parameter = "rel"
) |>
  format_ae_specific(
    filter_method = "percent",
    filter_criteria = 6
  ) |>
  tlf_ae_specific(
    source = "Source:  [CDISCpilot: adam-adsl; adae]",
    analysis = "ae_specific",
    meddra_version = "24.0",
    path_outtable = file.path(rtf_dir, "ae0specific4.rtf")
  )

## ----download-filtered-rtf, results="asis", echo=FALSE------------------------
cat(
  "Generated RTF file: ae0specific4.rtf"
)

## -----------------------------------------------------------------------------
prepare_ae_specific(
  meta,
  population = "apat",
  observation = "wk12",
  parameter = "rel"
) |>
  format_ae_specific(
    sort_order = "count_des",
    sort_column = "Placebo"
  ) |>
  tlf_ae_specific(
    source = "Source:  [CDISCpilot: adam-adsl; adae]",
    analysis = "ae_specific",
    meddra_version = "24.0",
    path_outtable = file.path(rtf_dir, "ae0specific5.rtf")
  )

## ----download-sorted-rtf, results="asis", echo=FALSE--------------------------
cat(
  "Generated RTF file: ae0specific5.rtf"
)

## -----------------------------------------------------------------------------
prepare_ae_specific(
  meta,
  population = "apat",
  observation = "wk12",
  parameter = "rel"
) |>
  format_ae_specific(
    filter_method = "percent",
    filter_criteria = 6,
    sort_order = "count_des",
    sort_column = "Placebo"
  ) |>
  tlf_ae_specific(
    source = "Source:  [CDISCpilot: adam-adsl; adae]",
    analysis = "ae_specific",
    meddra_version = "24.0",
    path_outtable = file.path(rtf_dir, "ae0specific6.rtf")
  )

## ----download-filtered-sorted-rtf, results="asis", echo=FALSE-----------------
cat(
  "Generated RTF file: ae0specific6.rtf"
)

