teal.modules.general (version 0.4.1)

tm_missing_data: teal module: Missing data analysis

Description

This module analyzes missing data in data.frames to help users explore missing observations and gain insights into the completeness of their data. It is useful for clinical data analysis within the context of CDISC standards and adaptable for general data analysis purposes.

Usage

tm_missing_data(
  label = "Missing data",
  plot_height = c(600, 400, 5000),
  plot_width = NULL,
  datanames = "all",
  parent_dataname = "ADSL",
  ggtheme = c("classic", "gray", "bw", "linedraw", "light", "dark", "minimal", "void"),
  ggplot2_args = list(`Combinations Hist` = teal.widgets::ggplot2_args(labs =
    list(caption = NULL)), `Combinations Main` = teal.widgets::ggplot2_args(labs =
    list(title = NULL))),
  pre_output = NULL,
  post_output = NULL,
  transformators = list(),
  decorators = list()
)

Value

Object of class teal_module to be used in teal applications.

Arguments

label

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

plot_height

(numeric) optional, specifies the plot height as a three-element vector of value, min, and max intended for use with a slider UI element.

plot_width

(numeric) optional, specifies the plot width as a three-element vector of value, min, and max for a slider encoding the plot width.

datanames

(character) Names of the datasets relevant to the item. There are 2 reserved values that have specific behaviors:

• The keyword "all" includes all datasets available in the data passed to the teal application.

• NULL hides the sidebar panel completely.

• If transformators are specified, their datanames are automatically added to this datanames argument.

parent_dataname

(character(1)) Specifies the parent dataset name. Default is ADSL for CDISC data. If provided and exists, enables additional analysis "by subject". For non-CDISC data, this parameter can be ignored.

ggtheme

(character) optional, specifies the default ggplot2 theme for plots. Defaults to classic.

ggplot2_args

(ggplot2_args) optional, object created by teal.widgets::ggplot2_args() with settings for all the plots or named list of ggplot2_args objects for plot-specific settings. The argument is merged with options variable teal.ggplot2_args and default module setup.

List names should match the following: c("default", "Summary Obs", "Summary Patients", "Combinations Main", "Combinations Hist", "By Subject").

For more details see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets").

pre_output

(shiny.tag) optional, text or UI element to be displayed before the module's output, providing context or a title. with text placed before the output to put the output into context. For example a title.

post_output

(shiny.tag) optional, text or UI element to be displayed after the module's output, adding context or further instructions. Elements like shiny::helpText() are useful.

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").

decorators

(named list of lists of teal_transform_module) optional, decorator for tables or plots included in the module output reported. The decorators are applied to the respective output objects.

See section "Decorating Module" below for more details.

Decorating Module

This module generates the following objects, which can be modified in place using decorators:

• summary_plot (grob created with ggplot2::ggplotGrob())

• combination_plot (grob created with ggplot2::ggplotGrob())

• by_subject_plot (ggplot)

• table (datatables created with DT::datatable())

A Decorator is applied to the specific output using a named list of teal_transform_module objects. The name of this list corresponds to the name of the output to which the decorator is applied. See code snippet below:

tm_missing_data(
   ..., # arguments for module
   decorators = list(
     summary_plot = teal_transform_module(...), # applied only to `summary_plot` output
     combination_plot = teal_transform_module(...), # applied only to `combination_plot` output
     by_subject_plot = teal_transform_module(...), # applied only to `by_subject_plot` output
     table = teal_transform_module(...) # applied only to `table` output
   )
)

For additional details and examples of decorators, refer to the vignette vignette("decorate-module-output", package = "teal.modules.general").

To learn more please refer to the vignette vignette("transform-module-output", package = "teal") or the teal::teal_transform_module() documentation.

Examples in Shinylive

example-1

Open in Shinylive

example-2

Open in Shinylive

Examples

# general example data
data <- teal_data()
data <- within(data, {
  require(nestcolor)

  add_nas <- function(x) {
    x[sample(seq_along(x), floor(length(x) * runif(1, .05, .17)))] <- NA
    x
  }

  iris <- iris
  mtcars <- mtcars

  iris[] <- lapply(iris, add_nas)
  mtcars[] <- lapply(mtcars, add_nas)
  mtcars[["cyl"]] <- as.factor(mtcars[["cyl"]])
  mtcars[["gear"]] <- as.factor(mtcars[["gear"]])
})

app <- init(
  data = data,
  modules = modules(
    tm_missing_data(parent_dataname = "mtcars")
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# CDISC example data
data <- teal_data()
data <- within(data, {
  require(nestcolor)
  ADSL <- teal.data::rADSL
  ADRS <- rADRS
})
join_keys(data) <- default_cdisc_join_keys[names(data)]

app <- init(
  data = data,
  modules = modules(
    tm_missing_data()
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}