--- title: "Build an Interactive Baseline Characteristic Table" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Build an Interactive Baseline Characteristic Table} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, message=FALSE} library(r2rtf) library(metalite) library(metalite.ae) library(metalite.sl) ``` There are 2 key metadata types: - metadata for the baseline characteristic table - metadata for the AE subgroup specific table # Build metadata {.tabset} ## Metadata for baseline characteristic table The code below is the same as `meta_sl_example()`. ```{r} adsl <- r2rtf::r2rtf_adsl adsl$TRTA <- adsl$TRT01A adsl$TRTA <- factor(adsl$TRTA, levels = c("Placebo", "Xanomeline Low Dose", "Xanomeline High Dose"), labels = c("Placebo", "Low Dose", "High Dose") ) meta <- meta_adam( population = adsl, observation = adsl ) |> define_plan(plan = plan( analysis = "base_char", population = "apat", observation = "apat", parameter = "age;gender;race" )) |> define_population( name = "apat", group = "TRTA", subset = quote(SAFFL == "Y"), var = c("USUBJID", "TRTA", "SAFFL", "AGEGR1", "SEX", "RACE") ) |> define_observation( name = "apat", group = "TRTA", subset = quote(SAFFL == "Y"), var = c("USUBJID", "TRTA", "SAFFL", "AGEGR1", "SEX", "RACE") ) |> define_parameter( name = "age", var = "AGE", label = "Age (years)", vargroup = "AGEGR1" ) |> define_parameter( name = "gender", var = "SEX", label = "Gender" ) |> define_parameter( name = "race", var = "RACE", label = "Race" ) |> define_analysis( name = "base_char", title = "Participant Baseline Characteristics by Treatment Group", label = "baseline characteristic table" ) |> meta_build() ``` ## A metadata of the AE subgroup specific analysis In this vignette, we will directly use the metadata built by `meta_ae_example()`. ```{r} meta_ae <- meta_ae_example() ``` # Build a reactable {.tabset} ## Baseline characteristic table + Participants With Drug-Related AE ```{r, eval = TRUE} react_base_char( metadata_sl = meta, metadata_ae = meta_ae, ae_subgroup = c("age", "race", "gender"), ae_specific = "rel", width = 1200 ) ``` ## Baseline characteristic table + Participants With Serious AE ```{r, eval=TRUE} react_base_char( metadata_sl = meta, metadata_ae = meta_ae, ae_subgroup = c("age", "race", "gender"), ae_specific = "ser", width = 1200 ) ```