[Question]: tm_t_summary() Error: Treatment values cannot contain empty strings

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The tm_t_summary requires that the input dataset cannot contain observations with empty ARM, otherwise the above ERROR will be reported. I tried to filter the data with filter = teal_slices(), but even though it's locked in the filter panel, it still shows an error.

A little confused about how to properly filter data for tm_t_summary. Many thanks!

I made more tests and also learned filter_panel_api, t it's true that teal_slice(dataname = "ADSL",expr="ARMCD=='ARM A'",id = "valid_arm", title = "Test NullARM") can pass the filter to tm_t_summary(); But it's a special case, if ADSL$ARM contains null value, this module tm_t_summary() failed to process it, wish for your further confirmation?

## Setup App
app <- teal::init(
  data = data,
  title = build_app_title("Safety Analysis Teal Demo App", nest_logo),
  header = header,
  footer = footer,
  # Set initial filter state as safety-evaluable population
  filter = teal_slices(
    count_type = "all",
    teal_slice(dataname = "ADSL", varname = "SAFFL", selected = "Y"),
    teal_slice(dataname = "ADSL",expr="ARMCD=='ARM A'",id = "valid_arm", title = "Test NullARM"),
    module_specific = TRUE,
    mapping = list(
      `Demographic Table` = "valid_arm"
    )
  ),
  modules = modules(
    tm_t_summary(
      label = "Demographic Table",
      dataname = "ADSL",
      arm_var =   choices_selected("ARM", "ARM"),
      summarize_vars = choices_selected(
        c("SEX", "RACE", "AGE"),
        selected = c("SEX", "AGE", "RACE")
      )
    )
  )
)

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library(teal.modules.general)
library(teal.modules.clinical)
options(shiny.useragg = FALSE)

## Data reproducible code ----

data <- within(teal_data(), {
  library(random.cdisc.data)
  library(dplyr)
  library(nestcolor)
  # optional libraries
  library(sparkline)
  
  ADSL <- radsl(seed = 1)
  ADSL <- ADSL %>%
    mutate(ARM = as.character(ARM)) %>%
    mutate(ARM = ifelse(ARM == "C: Combination", "", ARM)) %>%
    mutate(ARM = as.factor(ARM))
})

datanames <- c("ADSL")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]


## App header and footer ----
nest_logo <- "https://raw.githubusercontent.com/insightsengineering/hex-stickers/main/PNG/nest.png"
app_source <- "https://github.com/insightsengineering/teal.gallery/tree/main/safety"
gh_issues_page <- "https://github.com/insightsengineering/teal.gallery/issues"

header <- tags$span(
  style = "display: flex; align-items: center; justify-content: space-between; margin: 10px 0 10px 0;",
  tags$span("My first teal app", style = "font-size: 30px;"),
  tags$span(
    style = "display: flex; align-items: center;",
    tags$img(src = nest_logo, alt = "NEST logo", height = "45px", style = "margin-right:10px;"),
    tags$span(style = "font-size: 24px;", "NEST @ Roche")
  )
)

footer <- tags$p(
  "This teal app is brought to you by the NEST Team at Roche/Genentech.
        For more information, please visit:",
  tags$a(href = app_source, target = "_blank", "Source Code"), ", ",
  tags$a(href = gh_issues_page, target = "_blank", "Report Issues")
)

## Setup App
app <- teal::init(
  data = data,
  title = build_app_title("Safety Analysis Teal Demo App", nest_logo),
  header = header,
  footer = footer,
  # Set initial filter state as safety-evaluable population
  filter = teal_slices(
    count_type = "all",
    teal_slice(dataname = "ADSL", varname = "SAFFL", selected = "Y"),
    teal_slice(dataname = "ADSL",expr="ARMCD=='ARM A'",id = "valid_arm", title = "Test NullARM"),
    teal_slice(dataname = "ADSL", varname = "AGE"),
    module_specific = TRUE,
    mapping = list(
      `Demographic Table` = "valid_arm"
    )
  ),
  modules = modules(
    tm_front_page(
      label = "App Info",
      header_text = c("Info about input data source" = "This app uses CDISC ADaM datasets randomly generated by `random.cdisc.data` R packages"),
      tables = list(`NEST packages used in this demo app` = data.frame(
        Packages = c(
          "teal.modules.general",
          "teal.modules.clinical",
          "random.cdisc.data"
        )
      ))
    ),
    tm_data_table("Data Table"),
    tm_variable_browser("Variable Browser"),
    tm_t_summary(
      label = "Demographic Table",
      dataname = "ADSL",
      arm_var =   choices_selected("ARM", "ARM"),
      summarize_vars = choices_selected(
        c("SEX", "RACE", "AGE"),
        selected = c("SEX", "AGE", "RACE")
      )
    )
  )
)

shinyApp(app$ui, app$server)

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