sdtmval: Validate SDTM Domains
Provides a set of tools to assist statistical programmers
in validating Study Data Tabulation Model (SDTM) domain data sets.
Statistical programmers are required to validate that a SDTM data set domain
has been programmed correctly, per the SDTM Implementation Guide (SDTMIG) by
'CDISC' (<https://www.cdisc.org/standards/foundational/sdtmig>),
study specification, and study protocol using a process called double
programming. Double programming involves two different programmers
independently converting the raw electronic data cut (EDC) data into a SDTM
domain data table and comparing their results to ensure accurate
standardization of the data. One of these attempts is termed 'production'
and the other 'validation'. Generally, production runs are the official
programs for submittals and these are written in 'SAS'. Validation runs can
be programmed in another language, in this case 'R'.
| Version: |
0.4.1 |
| Depends: |
R (≥ 2.10) |
| Imports: |
dplyr, glue, haven, knitr, lubridate, magrittr, purrr, readxl, rlang, stats, stringr, tidyr, tidyselect, utils |
| Suggests: |
rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2023-10-23 |
| DOI: |
10.32614/CRAN.package.sdtmval |
| Author: |
Stephen Knapp 
[aut, cre, cph] |
| Maintainer: |
Stephen Knapp <stephen at knappconsultingllc.com> |
| BugReports: |
https://github.com/skgithub14/sdtmval/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/skgithub14/sdtmval,
https://skgithub14.github.io/sdtmval/ |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
sdtmval results |
Documentation:
Downloads:
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