# Create a AE Summary Mock-up Table

    library(metalite.ae)

This vignette demonstrates how to generate a static AE summary table reporting - The number and percentage of participants with any AEs by treatment group; - The number and percentage of participants with drug-related AEs by treatment group; - The number and percentage of participants with serious AEs by treatment group.

## Overview

Mock tables help reviewers evaluate a proposed table structure before final results are available. The `mock` argument of `format_ae_summary()` replaces the analysis values with placeholder values while preserving the AE summary layout.

The mock output is intended as a convenient starting point that resembles the planned table. It is not an all-encompassing mock table template, so additional customization may be needed for study-specific requirements.

## Define metadata

This example uses ADSL and ADAE data from the forestly package. The metadata follows the same approach used in the AE Summary in RTF format vignette.

    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_summary",
      population = "apat",
      observation = "wk12",
      parameter = "any;rel;ser"
    )

    meta <- metalite::meta_adam(observation = adae, population = adsl) |>
      metalite::define_plan(analysis_plan) |>
      metalite::define_population(
        name = "apat",
        var = c("USUBJID", "SAFFL", "TRT01A"),
        group = "TRT01A",
        subset = SAFFL == "Y",
        label = "All Participants as Treated"
      ) |>
      metalite::define_observation(
        name = "wk12",
        var = c(
          "USUBJID", "SAFFL", "TRTA", "AEDECOD", "AEBODSYS", "AEREL",
          "AESER"
        ),
        group = "TRTA",
        subset = SAFFL == "Y",
        label = "Weeks 0 to 12"
      ) |>
      metalite::define_parameter(
        name = "any",
        term1 = "",
        term2 = "",
        var = "AEDECOD",
        soc = "AEBODSYS",
        label = "All AEs"
      ) |>
      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_parameter(
        name = "ser",
        term1 = "Serious",
        term2 = "",
        subset = AESER == "Y",
        var = "AEDECOD",
        soc = "AEBODSYS",
        label = "Serious AEs"
      ) |>
      metalite::define_analysis(
        name = "ae_summary",
        title = "Adverse Event Summary"
      ) |>
      metalite::meta_build()

## Prepare a mock table

First, prepare the AE summary analysis. Passing `mock = TRUE` to `format_ae_summary()` then creates placeholder values for the formatted table.

The mock table retains the row labels and treatment-group structure derived from the metadata. This allows the layout to be reviewed without presenting the calculated analysis values as final results.

    rtf_dir <- if (dir.exists("vignettes/rtf")) "vignettes/rtf" else "rtf"
    rtf_file <- file.path(rtf_dir, "ae0summary3.rtf")

    prepare_ae_summary(
      meta,
      population = "apat",
      observation = "wk12",
      parameter = "any;rel;ser"
    ) |>
      format_ae_summary(mock = TRUE) |>
      tlf_ae_summary(
        source = "Source:  [CDISCpilot: adam-adsl; adae]",
        analysis = "ae_summary", # Provide analysis type defined in meta$analysis
        path_outtable = rtf_file
      )
    #> any
    #> rel
    #> ser
    #> The output is saved in/private/var/folders/yy/6bb11gtn52z0qwdg1_6kdbg00000gn/T/RtmpBCvLa1/Rbuild12c86435ade20/metalite.ae/vignettes/rtf/ae0summary3.rtf

Generated RTF file: ae0summary3.rtf