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Conduct internal validation of a clinical prediction model for a binary outcome. Produce bias corrected performance metrics (c-statistic, Brier score, calibration intercept/slope) via bootstrap (simple bootstrap, bootstrap optimism, .632 optimism) and cross-validation (CV optimism, CV average). Also includes functions to assess model stability via bootstrap resampling. See Steyerberg et al. (2001) <doi:10.1016/s0895-4356(01)00341-9>; Harrell (2015) <doi:10.1007/978-3-319-19425-7>; Riley and Collins (2023) <doi:10.1002/bimj.202200302>.
| Version: | 0.1.0 |
| Imports: | dcurves, graphics, grDevices, insight, marginaleffects, methods, pmcalibration, pROC, stats, parallel, pbapply, purrr |
| Suggests: | ggplot2, glmnet, Hmisc, knitr, rmarkdown, ranger, gbm, rms, mgcv, mice |
| Published: | 2025-03-18 |
| DOI: | 10.32614/CRAN.package.pminternal |
| Author: | Stephen Rhodes [aut, cre, cph] |
| Maintainer: | Stephen Rhodes <steverho89 at gmail.com> |
| BugReports: | https://github.com/stephenrho/pminternal/issues |
| License: | GPL-3 |
| URL: | https://github.com/stephenrho/pminternal, https://stephenrho.github.io/pminternal/ |
| NeedsCompilation: | no |
| Citation: | pminternal citation info |
| Materials: | README NEWS |
| CRAN checks: | pminternal results |
| Reference manual: | pminternal.pdf |
| Vignettes: |
Handling missing data (source, R code) Getting started with 'pminternal' (source, R code) More examples (source, R code) |
| Package source: | pminternal_0.1.0.tar.gz |
| Windows binaries: | r-devel: pminternal_0.1.0.zip, r-release: pminternal_0.1.0.zip, r-oldrel: pminternal_0.1.0.zip |
| macOS binaries: | r-devel (arm64): pminternal_0.1.0.tgz, r-release (arm64): pminternal_0.1.0.tgz, r-oldrel (arm64): pminternal_0.1.0.tgz, r-devel (x86_64): pminternal_0.1.0.tgz, r-release (x86_64): pminternal_0.1.0.tgz, r-oldrel (x86_64): pminternal_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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