pmsims: Simulation-Based Sample Size Tools for Prediction Models

Provides a flexible, simulation-based toolkit for exploring how much data are needed to develop reliable prediction models. It works by repeatedly generating data, fitting models, and evaluating performance to show how sample size affects predictive accuracy, calibration, and overfitting. The package supports continuous, binary, and time-to-event outcomes and can be used with both regression-based modelling approaches and machine-learning methods. It is designed to help researchers plan studies, assess feasibility, and build more robust and generalisable models. The methods are described in Olaniran et al. (2026) <doi:10.1186/s12874-026-02935-9> and Shamsutdinova et al. (2026) <doi:10.48550/arXiv.2602.23507>.

Version:	1.0.0
Depends:	R (≥ 4.1.0)
Imports:	cli, ggplot2, lifecycle, mlpwr, pROC, stats, survival, timeROC, utils
Suggests:	covr, DescTools, doParallel, foreach, glmnet, knitr, mlbench, mlr, randomForestSRC, ranger, rmarkdown, synthpop, testthat (≥ 3.0.0), tuneRanger, xgboost
Published:	2026-09-17
DOI:	10.32614/CRAN.package.pmsims (may not be active yet)
Author:	Ewan Carr [aut, cre], Gordon Forbes [aut], Ridwan Olaniran [aut], Diana Shamsutdinova [aut], Daniel Stahl [aut], Sarah Markham [aut], Felix Zimmer [aut]
Maintainer:	Ewan Carr <ewan.carr at kcl.ac.uk>
BugReports:	https://github.com/pmsims-package/pmsims/issues
License:	GPL (≥ 3)
URL:	https://pmsims-package.github.io/pmsims/, https://github.com/pmsims-package/pmsims
NeedsCompilation:	no
Citation:	pmsims citation info
Materials:	README, NEWS
CRAN checks:	pmsims results

Documentation:

Reference manual:	pmsims.html , pmsims.pdf
Vignettes:	Getting started with pmsims (source, R code)

Downloads:

Package source:	pmsims_1.0.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): pmsims_1.0.0.tgz, r-release (x86_64): pmsims_1.0.0.tgz, r-oldrel (x86_64): pmsims_1.0.0.tgz

Linking:

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