Teal module: Event rates adjusted for patient-years

Usage

tm_t_events_patyear(
  label,
  dataname,
  parentname = ifelse(inherits(arm_var, "data_extract_spec"),
    teal.transform::datanames_input(arm_var), "ADSL"),
  arm_var,
  events_var,
  paramcd,
  aval_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname,
    "AVAL"), "AVAL", fixed = TRUE),
  avalu_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname,
    "AVALU"), "AVALU", fixed = TRUE),
  add_total = TRUE,
  total_label = "All Patients",
  conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order =
    TRUE),
  drop_arm_levels = TRUE,
  pre_output = NULL,
  post_output = NULL,
  basic_table_args = teal.widgets::basic_table_args()
)

Arguments

label

(character)
menu item label of the module in the teal app.

dataname

(character)
analysis data used in teal module.

parentname

(character)
parent analysis data used in teal module, usually this refers to ADSL.

arm_var

(choices_selected or data_extract_spec)
object with all available choices and preselected option for variable names that can be used as arm_var. It defines the grouping variable(s) in the results table. If there are two elements selected for arm_var, second variable will be nested under the first variable.

events_var

(teal.transform::choices_selected() or teal.transform::data_extract_spec())
object with all event counts.

paramcd

(choices_selected or data_extract_spec)
variable value designating the studied parameter.

aval_var

(choices_selected or data_extract_spec)
object with all available choices and preselected option for the analysis variable.

avalu_var

(teal.transform::choices_selected() or teal.transform::data_extract_spec())
object with all available choices and preselected option for the analysis unit variable.

add_total

(logical)
whether to include column with total number of patients.

total_label

(string)
string to display as total column/row label if column/row is enabled (see add_total).

conf_level

(choices_selected)
object with all available choices and preselected option for the confidence level, each within range of (0, 1).

drop_arm_levels

(logical)
drop the unused arm_var levels. When TRUE, arm_var levels are set to those used in the dataname dataset. When FALSE, arm_var levels are set to those used in the parantname dataset.

pre_output

optional, (shiny.tag)
with text placed before the output to put the output into context. For example a title.

post_output

optional, (shiny.tag)
with text placed after the output to put the output into context. For example the shiny::helpText() elements are useful.

basic_table_args

optional, (basic_table_args)
object created by teal.widgets::basic_table_args() with settings for the module table. The argument is merged with option teal.basic_table_args and with default module arguments (hard coded in the module body).

For more details, see the vignette: vignette("custom-basic-table-arguments", package = "teal.widgets").

Examples

adsl <- tmc_ex_adsl
adaette <- tmc_ex_adaette %>%
  dplyr::filter(PARAMCD %in% c("AETTE1", "AETTE2", "AETTE3")) %>%
  dplyr::mutate(is_event = CNSR == 0) %>%
  dplyr::mutate(n_events = as.integer(is_event))

app <- init(
  data = cdisc_data(
    cdisc_dataset("ADSL", adsl),
    cdisc_dataset("ADAETTE", adaette)
  ),
  modules = modules(
    tm_t_events_patyear(
      label = "AE Rate Adjusted for Patient-Years At Risk Table",
      dataname = "ADAETTE",
      arm_var = choices_selected(
        choices = variable_choices(adsl, c("ARM", "ARMCD")),
        selected = "ARMCD"
      ),
      add_total = TRUE,
      events_var = choices_selected(
        choices = variable_choices(adaette, "n_events"),
        selected = "n_events",
        fixed = TRUE
      ),
      paramcd = choices_selected(
        choices = value_choices(adaette, "PARAMCD", "PARAM"),
        selected = "AETTE1"
      )
    )
  )
)
#> [INFO] 2023-08-14 14:44:18.3006 pid:1183 token:[] teal.modules.clinical Initializing tm_t_events_patyear
if (interactive()) {
  shinyApp(app$ui, app$server)
}