The CDISC
Analysis Results Standard aims to facilitate automation,
reproducibility, reusability, and traceability of analysis results data
(ARD). The {cards} package creates these **C**DISC
**A**nalysis **R**esult **D**ata
**S**ets.

Use cases:

Quality Control (QC) of existing tables and figures.

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

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

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

Install cards from CRAN with:

`install.packages("cards")`

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

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

The {cards} package exports three types of functions:

Functions to create basic ARD objects.

Utilities to create new ARD objects.

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.

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
```