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cards

The CDISC Analysis Results Standard aims to facilitate automation, reproducibility, reusability, and traceability of analysis results data (ARD). The {cards} package creates these CDISC Analysis Result Data Sets.

Use cases:

1. Quality Control (QC) of existing tables and figures.

2. Pre-calculate statistics to be summarized in tables and figures.

3. Medical writers may easily access statistics and place in reports without copying and pasting from reports.

4. Provides a consistent format for results and lends results to be combined across studies for re-use and re-analysis.

Installation

Install cards from CRAN with:

install.packages("cards")

You can install the development version of cards from GitHub with:

# install.packages("devtools")
devtools::install_github("insightsengineering/cards")

Extensions

The {cards} package exports three types of functions:

1. Functions to create basic ARD objects.

2. Utilities to create new ARD objects.

3. Functions to work with existing ARD objects.

The {cardx} R package is an extension to {cards} that uses the utilities from {cards} and exports functions for creating additional ARD objects––including functions to summarize t-tests, Wilcoxon Rank-Sum tests, regression models, and more.

Getting Started

Review the Getting Started page for examples using ARDs to calculate statistics to later include in tables.

library(cards)

ard_continuous(ADSL, by = "ARM", variables = "AGE")
#> {cards} data frame: 24 x 10
#>    group1 group1_level variable stat_name stat_label   stat
#> 1     ARM      Placebo      AGE         N          N     86
#> 2     ARM      Placebo      AGE      mean       Mean 75.209
#> 3     ARM      Placebo      AGE        sd         SD   8.59
#> 4     ARM      Placebo      AGE    median     Median     76
#> 5     ARM      Placebo      AGE       p25         Q1     69
#> 6     ARM      Placebo      AGE       p75         Q3     82
#> 7     ARM      Placebo      AGE       min        Min     52
#> 8     ARM      Placebo      AGE       max        Max     89
#> 9     ARM    Xanomeli…      AGE         N          N     84
#> 10    ARM    Xanomeli…      AGE      mean       Mean 74.381
#> ℹ 14 more rows
#> ℹ Use `print(n = ...)` to see more rows
#> ℹ 4 more variables: context, fmt_fn, warning, error

Other Resources

• Posit 2024 pharmaverse Workshop: Follow the link for “Analysis Results Datasets” in the schedule.

• 2024 China Pharma R User Conference Keynote Address

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.