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Teal module for the AE overview

Source: R/tm_g_ae_oview.R
tm_g_ae_oview.Rd

Display the AE overview plot as a shiny module

Usage 

tm_g_ae_oview(
  label,
  dataname,
  arm_var,
  flag_var_anl,
  fontsize = c(5, 3, 7),
  plot_height = c(600L, 200L, 2000L),
  plot_width = NULL,
  transformators = list()
)

Arguments

label

(character(1)) Label shown in the navigation item for the module or module group. For modules() defaults to "root". See Details.

dataname

(character(1))
analysis data used in the teal module, needs to be available in the list passed to the data argument of teal::init().

arm_var

(choices_selected)
object with all available choices and the pre-selected option for variable names that can be used as arm_var. See teal.transform::choices_selected() for details. Column arm_var in the dataname has to be a factor.

flag_var_anl

(teal.transform::choices_selected) choices_selected object with variables used to count adverse event sub-groups (e.g. Serious events, Related events, etc.)

fontsize

(numeric(1) or numeric(3))
Defines initial possible range of font-size. fontsize is set for teal.widgets::optionalSliderInputValMinMax() which controls font-size in the output plot.

plot_height

(numeric(3))
vector to indicate default value, minimum and maximum values.

plot_width

(numeric(3))
vector to indicate default value, minimum and maximum values.

transformators

(list of teal_transform_module) that will be applied to transform module's data input. To learn more check vignette("transform-input-data", package = "teal").

Value

the teal::module() object.

Reporting

This module returns an object of class teal_module, that contains a server function. Since the server function returns a teal_report object, this makes this module reportable, which means that the reporting functionality will be turned on automatically by the teal framework.

For more information on reporting in teal, see the vignettes:

Examples 

data <- teal_data() %>%
  within({
    library(dplyr)
    ADSL <- rADSL
    ADAE <- rADAE
    .add_event_flags <- function(dat) {
      dat <- dat %>%
        mutate(
          TMPFL_SER = AESER == "Y",
          TMPFL_REL = AEREL == "Y",
          TMPFL_GR5 = AETOXGR == "5",
          AEREL1 = (AEREL == "Y" & ACTARM == "A: Drug X"),
          AEREL2 = (AEREL == "Y" & ACTARM == "B: Placebo")
        )
      labels <- c(
        "Serious AE", "Related AE", "Grade 5 AE",
        "AE related to A: Drug X", "AE related to B: Placebo"
      )
      cols <- c("TMPFL_SER", "TMPFL_REL", "TMPFL_GR5", "AEREL1", "AEREL2")
      for (i in seq_along(labels)) {
        attr(dat[[cols[i]]], "label") <- labels[i]
      }
      dat
    }
    ADAE <- .add_event_flags(ADAE)
  })

join_keys(data) <- default_cdisc_join_keys[names(data)]

ADAE <- data[["ADAE"]]

app <- init(
  data = data,
  modules = modules(
    tm_g_ae_oview(
      label = "AE Overview",
      dataname = "ADAE",
      arm_var = choices_selected(
        selected = "ACTARM",
        choices = c("ACTARM", "ACTARMCD")
      ),
      flag_var_anl = choices_selected(
        selected = "AEREL1",
        choices = variable_choices(
          ADAE,
          c("TMPFL_SER", "TMPFL_REL", "TMPFL_GR5", "AEREL1", "AEREL2")
        ),
      ),
      plot_height = c(600, 200, 2000)
    )
  )
)
#> Initializing tm_g_ae_oview
if (interactive()) {
  shinyApp(app$ui, app$server)
}