⚠️ WARNING: scda is deprecated and no longer maintained. Use at your own risk.

scda: Synthetic CDISC Data Archive Accessor Functions

This R package contains functions for accessing synthetic CDISC from data archive packages such as scda.2022. At least one of the archive packages should be installed in order to use this package.

This synthetic data can be used as test data when developing teal applications or, statistical analysis functions. Due to the data not being derived from a real clinical trials, it provides an excellent method for generating reproducible examples when reporting errors.

Note however, that this data is somewhat idealized and real trial data is often significantly more complex.

Installation

It is recommended that you create and use a Github PAT to install the latest version of this package. Once you have the PAT, run the following:

Sys.setenv(GITHUB_PAT = "your_access_token_here")
if (!require("remotes")) install.packages("remotes")
remotes::install_github("insightsengineering/scda@*release")

A stable release of all NEST packages from June 2022 is also available here.

To install scda.2022, run the following:

Sys.setenv(GITHUB_PAT = "your_access_token_here")
if (!require("remotes")) install.packages("remotes")
remotes::install_github("insightsengineering/scda.2022@*release")

Please see the scda.2022 package website for more details.

Basic Usage

You can see which data are available with

library(scda)
ls_synthetic_cdisc_data()

And to load a specific data archive use

# chose the first one
chosen_data_archive <- ls_synthetic_cdisc_data()$Name[1]
print(chosen_data_archive)
oldest_dfs <- synthetic_cdisc_data(chosen_data_archive)
names(oldest_dfs)

# chose the latest one
latest_dfs <- synthetic_cdisc_data("latest")
names(latest_dfs)

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