teal Module: Generalized Estimating Equations (GEE) analysis

This module produces an analysis table using Generalized Estimating Equations (GEE).

Usage

tm_a_gee(
  label,
  dataname,
  parentname = ifelse(inherits(arm_var, "data_extract_spec"),
    teal.transform::datanames_input(arm_var), "ADSL"),
  aval_var,
  id_var,
  arm_var,
  visit_var,
  cov_var,
  arm_ref_comp = NULL,
  paramcd,
  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()
)

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.
aval_var: (teal.transform::choices_selected())
object with all available choices and pre-selected option for the analysis variable.
id_var: (teal.transform::choices_selected())
object specifying the variable name for subject id.
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.
visit_var: (teal.transform::choices_selected())
object with all available choices and preselected option for variable names that can be used as visit variable. Must be a factor in dataname.
cov_var: (teal.transform::choices_selected())
object with all available choices and preselected option for the covariates variables.
arm_ref_comp: (list) optional,
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.
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: (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.

Examples

library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following object is masked from ‘package:testthat’:
#> 
#>     matches
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
data <- teal_data()
data <- within(data, {
  ADSL <- tmc_ex_adsl
  ADQS <- tmc_ex_adqs %>%
    filter(ABLFL != "Y" & ABLFL2 != "Y") %>%
    mutate(
      AVISIT = as.factor(AVISIT),
      AVISITN = rank(AVISITN) %>%
        as.factor() %>%
        as.numeric() %>%
        as.factor(),
      AVALBIN = AVAL < 50 # Just as an example to get a binary endpoint.
    ) %>%
    droplevels()
})
datanames <- c("ADSL", "ADQS")
datanames(data) <- datanames
join_keys(data) <- default_cdisc_join_keys[datanames]

app <- init(
  data = data,
  modules = modules(
    tm_a_gee(
      label = "GEE",
      dataname = "ADQS",
      aval_var = choices_selected("AVALBIN", fixed = TRUE),
      id_var = choices_selected(c("USUBJID", "SUBJID"), "USUBJID"),
      arm_var = choices_selected(c("ARM", "ARMCD"), "ARM"),
      visit_var = choices_selected(c("AVISIT", "AVISITN"), "AVISIT"),
      paramcd = choices_selected(
        choices = value_choices(data[["ADQS"]], "PARAMCD", "PARAM"),
        selected = "FKSI-FWB"
      ),
      cov_var = choices_selected(c("BASE", "AGE", "SEX", "BASE:AVISIT"), NULL)
    )
  )
)
#> Initializing tm_a_gee (prototype)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

teal Module: Generalized Estimating Equations (GEE) analysis

Usage

Arguments

Value

See also

Examples