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bayespmtools: Bayesian Sample Size and Precision Considerations for Risk Prediction Models

Performs Bayesian sample size, precision, and value-of-information analysis for external validation of existing multi-variable prediction models using the approach proposed by Sadatsafavi and colleagues (2025) <doi:10.1002/sim.70389>.

Version: 0.0.1
Depends: R (≥ 3.5.0)
Imports: fastLogisticRegressionWrap, logitnorm, mc2d, mcmapper, pROC, cobs, OOR, quantreg
Suggests: knitr, rmarkdown, ggplot2
Published: 2026-03-29
DOI: 10.32614/CRAN.package.bayespmtools
Author: Mohsen Sadatsafavi ORCID iD [aut, cre], Anna Luo [ctb]
Maintainer: Mohsen Sadatsafavi <mohsen.sadatsafavi at ubc.ca>
License: GPL-3
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: bayespmtools results

Documentation:

Reference manual: bayespmtools.html , bayespmtools.pdf
Vignettes: bayespmtools_tutorial (source, R code)
Getting Started with bayespmtools (source, R code)

Downloads:

Package source: bayespmtools_0.0.1.tar.gz
Windows binaries: r-devel: bayespmtools_0.0.1.zip, r-release: bayespmtools_0.0.1.zip, r-oldrel: bayespmtools_0.0.1.zip
macOS binaries: r-release (arm64): bayespmtools_0.0.1.tgz, r-oldrel (arm64): not available, r-release (x86_64): bayespmtools_0.0.1.tgz, r-oldrel (x86_64): bayespmtools_0.0.1.tgz

Linking:

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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.