Matrix of Scatterplots module • dv.explorer.parameter

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

The boxplotscatterplotmatrix module makes it possible to visualize a matrix of scatterplots of parameters that also includes correlation stats.

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

scatterplotmatrix features the following plot and tables:

A matrix of scatterplots with some correlation statistics.

It supports bookmarking.

Arguments for the module

dv.explorer.parameter::mod_scatterplotmatrix() 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_scatterplotmatrix() for the complete list of arguments and their description.

Input menus

A set of menus allows to select a set of parameters and grouping.

Visualizations

A matrix of scatterplots

This visualizations consists of a matrix of scatterplots with correlation statistics.

Creating a scatterplotmatrix 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(
    "Scatterplot Matrix" = dv.explorer.parameter::mod_scatterplotmatrix(
      "scatterplotmatrix",
      bm_dataset_name = "adbm",
      group_dataset_name = "adsl",
      subjid_var = "USUBJID",
      cat_var = "PARCAT1"
    )
  ),
  filter_data = "adsl",
  filter_key = "USUBJID"
)