A set of Study Data Tabulation Model (SDTM) datasets from the Clinical Data Interchange Standards Consortium (CDISC) pilot project used for testing and developing Analysis Data Model (ADaM) derivations inside the 'admiral' package.
admiral.test v0.7.0 will be the final version. At the end of 2023, the package will be archived in favor of pharmaversesdtm.Test data for the {admiral} package taken from the CDISC pilot project and renamed with admiral_ prefix for clarity.
As this mostly contains safety data only, we extend this as needed by adding further test data required such as for PK and TA-specific efficacy analyses.
See the "How To Update" section below for more details.
The package is available from CRAN and can be installed by running install.packages("admiral.test").
To install the latest development version of the package directly from GitHub use the following code:
if (!requireNamespace("remotes", quietly = TRUE)) {
install.packages("remotes")
}
remotes::install_github("pharmaverse/admiral.test", ref = "devel")
Firstly, make a GitHub issue in this repo with the planned updates and tag @pharmaverse/admiral so that one of the development core team can sanity check the request.
Then there are two main ways to extend the test data, either by adding new datasets or extending existing datasets with new records/variables. Whichever method you choose, it is worth noting the following:
dev/ folder.library() at the start of the program (but please do not call library(admiral.test)).renv.lock file, so they will already be installed if you have been keeping in sync--you can check this by entering renv::status() in the Console. However, you may also wish to install {metatools} and {ggplot2}, which are currently not specified in the renv.lock file. If you feel that you need to install any other packages in addition to those just mentioned, then please tag @pharmaverse/admiral to discuss with the development core team.dev/ folder, you need to run it as a standalone R script, in order to generate a test dataset that will become part of the {admiral.test} package, but you do not need to build the package..rda file whose name is consistent with the name of the dataset: for example, the dataset dm should be renamed to raw_dm before saving it as raw_dm.rda; if you save dm as raw_dm.rda and subsequently load the .rda file, then dm (not raw_dm) will be loaded into the global environment.dev/ are stored within the {admiral.test} GitHub repository, but they are not part of the {admiral.test} package--the dev/ folder is specified in .Rbuildignore.dev/ folder, you generate a dataset that is written to the data/ folder, which will become part of the {admiral.test} package.R/data.R, for the purpose of generating documentation in the man/ folder.dev/ folder, named <name>.R, where <name> is the SDTM domain name, (e.g. rs.R), to generate the test data and output admiral_<name>.rda to the data/ folder. Use CDISC pilot data such as admiral_dm as input in this program in order to create realistic synthetic data that remains consistent with other domains. Note that no personal data should be used as part of this package, even if anonymized.admiral_<name> in R/data.R.devtools::document() in order to update NAMESPACE and update the .Rd files in man/.raw_<name>, where <name> is the SDTM domain name (e.g. rename ds to raw_ds), and then save it to the data/ folder as raw_<name>.rda (e.g. save(raw_ds, file = "data/raw_ds.rda")).dev/ folder, named update_<name>.R, to load raw_<name>.rda, make the updates, and output admiral_<name>.rda to the data/ folder.raw_<name> and admiral_<name> in R/data.R.devtools::document() in order to update NAMESPACE and update the .Rd files in man/.