Boxplot module • dv.explorer.parameter

This guide provides a detailed overview of the boxplot module and its features. It is meant to provide guidance to App Creators on creating Apps in DaVinci using the boxplot module. Walk-throughs for sample app creation using the module are also included to demonstrate the various module specific features.

The boxplot module makes it possible to visualize a boxplot chart of parameters, and several tables with population listings, summary statistics and between group stat comparisons.

Pre-requisite:

“Parameter” Term Disambiguation

The guide uses the term “parameter” at several places. This term in the guide represents clinical analysis parameters and values such as laboratory values, safety values, etc as used in the clinical dataset context. This can be confused with the word parameter as used in a programming context - “parameters of a function”. Therefore, to fully disambiguate the usage in this guide:

Parameter is used exclusively in the clinical dataset context
Argument is used to represent parameter of a function in the programming context

Features

boxplot features the following plot and tables:

A set of boxplot/violin charts with different custom groupings and optionally showing the individual data points.
A table showing the population listing of the selected boxplot
A table showing the number of subjects per boxplot
A table showing the number of subjects per boxplot and addition stats on the parameter value distribution
A table containing a set of statistical tests comparing the mean parameter value between groups

It supports bookmarking.

Arguments for the module

dv.explorer.parameter::mod_boxplot() module uses several arguments with the following being mandatory and the rest optional. As part of app creation, the app creator should specify the values for these arguments as applicable.

Mandatory Arguments

module_id : A unique identifier of type character for the module in the app.
subjid_var: A common column across all datasets that uniquely identify subjects. By default: “SUBJID”
bm_dataset_name: The dataset that contains the continuous parameters. It expects a dataset similar to https://www.cdisc.org/kb/examples/adam-basic-data-structure-bds-using-paramcd-80288192 , 1 record per subject per parameter per analysis visit

It expects, at least, the columns passed in the arguments, subjid_var, cat_var, par_var, visit_var and value_vars.
group_dataset_name:

It expects a dataset with an structure similar to https://www.cdisc.org/kb/examples/adam-subject-level-analysis-adsl-dataset-80283806 , one record per subject It expects to contain, at least, subjid_var

Refer to dv.explorer.parameter::mod_boxplot() for the complete list of arguments and their description.

Input menus

A set of menus allows to select a set of parameters, groupings and settings of the visualization.

Visualizations

Boxplot

This visualizations consists of a facetted boxplot plot based on the set of parameters and grouping variable.

Tables

Population listing and single listing

A table containing a listing of the population of a single boxplot selected by clicking, and a table containing a single subject selected by double clicking on an individual data point in the boxplot.

The single subject table contains a drill down button that can be used to obtain more information about the subject. This setting requires additional configuration.

Count table

A table containing the number of subjects per boxplot.

Summary table

A table containing a set of summary statistics per boxplot.

Significance table

A table containing a set of statistical tests comparing the means of different groups.

Creating a boxplot application

adbm_dataset <- dv.explorer.parameter::adbm_example %>%
  dplyr::mutate(
    USUBJID = factor(USUBJID),
    PARCAT1 = factor(PARCAT1),
    PARAM = factor(PARAM),
    AVISIT = factor(AVISIT)
  )

adsl_dataset <- dv.explorer.parameter::adsl_example %>%
  dplyr::mutate(USUBJID = factor(USUBJID))

dv.manager::run_app(
  data = list(dummy = list(adbm = adbm_dataset, adsl = adsl_dataset)),
  module_list = list(
    Boxplot = dv.explorer.parameter::mod_boxplot(
      "boxplot",
      bm_dataset_name = "adbm",
      group_dataset_name = "adsl",
      subjid_var = "USUBJID",
      cat_var = "PARCAT1"
    )
  ),
  filter_data = "adsl",
  filter_key = "USUBJID"
)

Drill down functionality

This module allows passing the subject_id to another module for further drill down when the View Details button is pressed.