integrity: Tests Checking for Implausible Values in Clinical Trials Data
Sixteen individual participant data-specific checks in a report-style result. Items are automated where possible, and are grouped into eight domains, including unusual data patterns, baseline characteristics, correlations, date violations, patterns of allocation, internal and external inconsistencies, and plausibility of data. The package may be applied by evidence synthesists, editors, and others to determine whether a randomised controlled trial may be considered trustworthy to contribute to the evidence base that informs policy and practice. For more details, see Hunter et al. (2024) <doi:10.1002/jrsm.1738> and <doi:10.32614/RJ-2017-008> in the same issue of Research Synthesis Methods.
| Version: |
1.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
ggplot2, dplyr, janitor, gtsummary, ggpubr, lubridate, car, rlang |
| Suggests: |
knitr, readxl, yaml |
| Published: |
2026-04-08 |
| DOI: |
10.32614/CRAN.package.integrity (may not be active yet) |
| Author: |
Sol Libesman [aut],
Kylie Hunter [aut],
David Nguyen [aut],
Dario Strbenac [aut, cre],
Jie Kang [aut] |
| Maintainer: |
Dario Strbenac <dario.strbenac at sydney.edu.au> |
| License: |
GPL-3 |
| URL: |
https://github.sydney.edu.au/Charles-Perkins-Centre-Data-Science-Hub/CPCDASH0010 |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
integrity results |
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