boxly

Installation

The easiest way to get boxly is to install from CRAN:

install.packages("boxly")

Alternatively, to use a new feature or get a bug fix, you can install the development version of boxly from GitHub:

# install.packages("remotes")
remotes::install_github("Merck/boxly")

Overview

The boxly package creates interactive box plots for clinical trial analysis & reporting.

02.06.2023_14.17.00_REC.mp4

We assume ADaM datasets are ready for analysis and leverage metalite data structure to define inputs and outputs.

Workflow

The general workflow is:

1. Use the metalite package to construct input metadata from ADaM datasets.
2. Use prepare_boxly() to prepare datasets for interactive box plot.
3. Use boxly() to generate an interactive box plot.

Here is a quick example using an example dataset:

library("boxly")

analysis_plan <- metalite::plan(
  analysis = "boxly",
  population = "apat",
  observation = "wk12",
  parameter = "SODIUM"
)

meta <- metalite::meta_adam(
  population = boxly_adsl,
  observation = boxly_adlb
) |>
  metalite::define_plan(analysis_plan) |>
  metalite::define_population(
    name = "apat",
    group = "TRTA",
    subset = SAFFL == "Y",
    label = "Safety Population"
  ) |>
  metalite::define_observation(
    name = "wk12",
    group = "TRTA",
    var = "PARAM",
    subset = AVISITN <= 12 & !is.na(CHG),
    label = "Weeks 0 to 12"
  ) |>
  metalite::define_parameter(
    name = "SODIUM",
    label = "Sodium (mmol/L)",
    subset = PARAMCD == "SODIUM"
  ) |>
  metalite::define_analysis(
    name = "boxly",
    label = "Interactive Box Plot",
    x = "AVISITN",
    y = "CHG"
  ) |>
  metalite::meta_build()

meta |>
  prepare_boxly() |>
  boxly()

Highlighted features

• Parameter selection: Drop-down menu to select parameter of interest.
• Interactivity: Display summary statistics and outlier information interactively.
• Listing: Provide detailed information in interactive listing.