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teal Module: Event Rates Adjusted for Patient-Years

Source: R/tm_t_events_patyear.R
tm_t_events_patyear.Rd

This module produces a table of 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 = default_total_label(),
  na_level = default_na_str(),
  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

(teal.transform::choices_selected())
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())
object with all available choices and preselected option for the variable with all event counts.

paramcd

(teal.transform::choices_selected())
object with all available choices and preselected option for the parameter code variable from dataname.

aval_var

(teal.transform::choices_selected())
object with all available choices and pre-selected option for the analysis variable.

avalu_var

(teal.transform::choices_selected())
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). Defaults to "All Patients". To set a new default total_label to apply in all modules, run set_default_total_label("new_default").

na_level

(string)
used to replace all NA or empty values in character or factor variables in the data. Defaults to "<Missing>". To set a default na_level to apply in all modules, run set_default_na_str("new_default").

conf_level

(teal.transform::choices_selected())
object with all available choices and pre-selected option for the confidence level, each within range of (0, 1).

drop_arm_levels

(logical)
whether to drop unused levels of arm_var. If TRUE, arm_var levels are set to those used in the dataname dataset. If FALSE, arm_var levels are set to those used in the parentname dataset. If dataname and parentname are the same, then drop_arm_levels is set to TRUE and user input for this parameter is ignored.

pre_output

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

post_output

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

basic_table_args

(basic_table_args) optional
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").

Value

a teal_module object.

See also

The TLG Catalog where additional example apps implementing this module can be found.

Examples in Shinylive

example-1

Open in Shinylive

example-2

Open in Shinylive

Examples 

library(dplyr)

data <- teal_data()
data <- within(data, {
  ADSL <- tmc_ex_adsl
  ADAETTE <- tmc_ex_adaette %>%
    filter(PARAMCD %in% c("AETTE1", "AETTE2", "AETTE3")) %>%
    mutate(is_event = CNSR == 0) %>%
    mutate(n_events = as.integer(is_event))
})
join_keys(data) <- default_cdisc_join_keys[names(data)]

ADSL <- data[["ADSL"]]
ADAETTE <- data[["ADAETTE"]]

# 1. Basic Example

app <- init(
  data = data,
  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"
      )
    )
  )
)
#> Initializing tm_t_events_patyear
#> Initializing reporter_previewer_module
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# 2. Example with table split on 2 arm_var variables

app <- init(
  data = data,
  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", "SEX")),
        selected = c("ARM", "SEX")
      ),
      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"
      )
    )
  )
)
#> Initializing tm_t_events_patyear
#> Initializing reporter_previewer_module
if (interactive()) {
  shinyApp(app$ui, app$server)
}