Monitoring reporting rates of subject-level clinical events (e.g. adverse events, protocol deviations) reported by clinical trial sites is an important aspect of risk-based quality monitoring strategy. Sites that are under-reporting or over-reporting events can be detected using bootstrap simulations during which patients are redistributed between sites. Site-specific distributions of event reporting rates are generated that are used to assign probabilities to the observed reporting rates. (Koneswarakantha 2024 <doi:10.1007/s43441-024-00631-8>).
| Version: | 1.0.0 |
| Depends: | R (≥ 4.0),ggplot2 |
| Imports: | dplyr (≥ 1.1.0),tidyr (≥ 1.1.0),magrittr,purrr,rlang,stringr,forcats,cowplot,RColorBrewer,furrr (≥ 0.2.1),progressr,knitr,tibble,dbplyr,glue |
| Suggests: | testthat,devtools,pkgdown,spelling,haven,vdiffr,lintr,DBI,duckdb,ggExtra |
| Published: | 2025-10-28 |
| DOI: | 10.32614/CRAN.package.simaerep |
| Author: | Bjoern Koneswarakantha [aut, cre, cph], F. Hoffmann-La Roche Ltd [cph] |
| Maintainer: | Bjoern Koneswarakantha <bjoern.koneswarakantha at roche.com> |
| License: | MIT + fileLICENSE |
| URL: | https://openpharma.github.io/simaerep/,https://github.com/openpharma/simaerep/ |
| NeedsCompilation: | no |
| Language: | en-US |
| Materials: | README,NEWS |
| CRAN checks: | simaerep results |