teal.modules.clinical (version 0.9.0)

tm_t_logistic: teal Module: Logistic Regression

Description

This module produces a multi-variable logistic regression table consistent with the TLG Catalog template LGRT02 available here.

Usage

tm_t_logistic(
  label,
  dataname,
  parentname = ifelse(inherits(arm_var, "data_extract_spec"),
    teal.transform::datanames_input(arm_var), "ADSL"),
  arm_var = NULL,
  arm_ref_comp = NULL,
  paramcd,
  cov_var = NULL,
  avalc_var = teal.transform::choices_selected(teal.transform::variable_choices(dataname,
    "AVALC"), "AVALC", fixed = TRUE),
  conf_level = teal.transform::choices_selected(c(0.95, 0.9, 0.8), 0.95, keep_order =
    TRUE),
  pre_output = NULL,
  post_output = NULL,
  basic_table_args = teal.widgets::basic_table_args()
)

Value

a teal_module object.

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() or NULL)
object with all available choices and preselected option for variable names that can be used as arm_var. This defines the grouping variable(s) in the results table. If there are two elements selected for arm_var, the second variable will be nested under the first variable. If NULL, no arm/treatment variable is included in the logistic model.

arm_ref_comp

optional, (list)
If specified it must be a named list with each element corresponding to an arm variable in ADSL and the element must be another list (possibly with delayed teal.transform::variable_choices() or delayed teal.transform::value_choices() with the elements named ref and comp that the defined the default reference and comparison arms when the arm variable is changed.

paramcd

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

cov_var

(teal.transform::choices_selected())
object with all available choices and preselected option for the covariates variables.

avalc_var

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

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).

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").

See Also

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

Examples

library(dplyr)

ADSL <- tmc_ex_adsl
ADRS <- tmc_ex_adrs %>%
  filter(PARAMCD %in% c("BESRSPI", "INVET"))

arm_ref_comp <- list(
  ACTARMCD = list(
    ref = "ARM B",
    comp = c("ARM A", "ARM C")
  ),
  ARM = list(
    ref = "B: Placebo",
    comp = c("A: Drug X", "C: Combination")
  )
)

app <- init(
  data = cdisc_data(
    ADSL = ADSL,
    ADRS = ADRS,
    code = "
      ADSL <- tmc_ex_adsl
      ADRS <- tmc_ex_adrs %>%
        filter(PARAMCD %in% c(\"BESRSPI\", \"INVET\"))
    "
  ),
  modules = modules(
    tm_t_logistic(
      label = "Logistic Regression",
      dataname = "ADRS",
      arm_var = choices_selected(
        choices = variable_choices(ADRS, c("ARM", "ARMCD")),
        selected = "ARM"
      ),
      arm_ref_comp = arm_ref_comp,
      paramcd = choices_selected(
        choices = value_choices(ADRS, "PARAMCD", "PARAM"),
        selected = "BESRSPI"
      ),
      cov_var = choices_selected(
        choices = c("SEX", "AGE", "BMRKR1", "BMRKR2"),
        selected = "SEX"
      )
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}