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Interactive box plot for clinical trial analysis

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# boxly <img src="man/figures/logo.png" align="right" width="120" />

[![R-CMD-check](https://github.com/Merck/boxly/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/Merck/boxly/actions/workflows/R-CMD-check.yaml)
[![Codecov test coverage](https://codecov.io/gh/Merck/boxly/branch/main/graph/badge.svg)](https://app.codecov.io/gh/Merck/boxly?branch=main)
[![CRAN status](https://www.r-pkg.org/badges/version/boxly)](https://cran.r-project.org/package=boxly)
[![CRAN Downloads](https://cranlogs.r-pkg.org/badges/boxly)](https://cran.r-project.org/package=boxly)

## Installation

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

```r
install.packages("boxly")
```

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

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

## Overview

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

</video>

We assume ADaM datasets are ready for analysis and
leverage [metalite](https://merck.github.io/metalite/) data structure to define
inputs and outputs.

## Workflow

The general workflow is:

1. Use `meta_boxly()` or metalite package to construct input metadata from ADaM datasets.
   For example,.
1. Use `prepare_boxly()` to prepare datasets for interactive box plot.
1. Use `boxly()` to generate an interactive box plot.

Here is a quick example using an example dataset:

```r
library("boxly")

meta_boxly(
  boxly_adsl,
  boxly_adlb,
  population_term = "apat",
  observation_term = "wk12",
  observation_subset = AVISITN <= 12 & !is.na(CHG)
) |>
  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.

boxly

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