stepwedgepower: Simulation-Based Power Evaluation for Stepped-Wedge Cluster Randomized Trials

Provides simulation-based power, type I error, and operating- characteristic evaluation for stepped-wedge cluster randomized trials. General binary-outcome designs support arbitrary crossover schedules, unequal clusters per sequence, secular trends, flexible cluster-period sizes, reproducible parallel execution, sensitivity grids, and mixed-model diagnostics. A component-based engine supports the four treatment states Control, A, B, and A+B under arbitrary asynchronous schedules, including structurally unobserved cluster-periods, withdrawal, reintroduction, wash-in delays, user-defined carryover decay, component main effects, an A-by-B interaction, estimability audits, multiplicity adjustment, conditional and failure-aware power, and explicit classification of hard model errors, nonconvergence, non-finite contrasts, singular fits, and successful fits. A batch-aware interface represents classic and batched stepped-wedge designs with delayed cluster initiation, structurally unobserved cluster-periods, and calendar-time, time-on-trial, or separate batch-specific time effects, following Kasza, Bowden, Hooper and Forbes (2022) <doi:10.1002/sim.9438>. The cumulative Control-to-A-to-A+B interface from earlier versions remains available. The design and mixed-effects analysis follow Hussey and Hughes (2007) <doi:10.1016/j.cct.2006.05.007>. Intraclass correlations for binary outcomes are converted to random-intercept standard deviations on the latent scale of the logistic-normal model, as reviewed by Eldridge, Ukoumunne and Carlin (2009) <doi:10.1111/j.1751-5823.2009.00092.x>. Monte Carlo uncertainty is reported using exact intervals from Clopper and Pearson (1934) <doi:10.1093/biomet/26.4.404>.

Version: 0.4.1
Imports: lme4, lifecycle, graphics, grDevices, stats, parallel, utils
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, swCRTdesign, swdpwr
Published: 2026-10-17
DOI: 10.32614/CRAN.package.stepwedgepower
Author: Lin (Amanda) Li [aut, cre], Florin Vaida [aut] (degree: PhD)
Maintainer: Lin (Amanda) Li <amandali14124277 at gmail.com>
BugReports: https://github.com/AmandaLinLi/stepwedgepower/issues
License: MIT + file LICENSE
URL: https://github.com/AmandaLinLi/stepwedgepower
NeedsCompilation: no
Citation: stepwedgepower citation info
Materials: README, NEWS
CRAN checks: stepwedgepower results

Documentation:

Reference manual: stepwedgepower.html , stepwedgepower.pdf
Vignettes: Asynchronous Control to A to A+B stepped-wedge designs (source, R code)
Classic and Batched Stepped-Wedge Designs (source, R code)
Benchmark Validation for Classic and Batched Stepped-Wedge Designs (source, R code)
Control, A, B, and A+B Designs with Withdrawal and Carryover (source, R code)
Case study: an Lp(a) testing stepped-wedge trial (source, R code)
Designing a stepped-wedge trial (source, R code)

Downloads:

Package source: stepwedgepower_0.4.1.tar.gz
Windows binaries: r-devel: stepwedgepower_0.1.3.zip, r-release: stepwedgepower_0.4.1.zip, r-oldrel: stepwedgepower_0.1.3.zip
macOS binaries: r-release (arm64): stepwedgepower_0.4.1.tgz, r-oldrel (arm64): stepwedgepower_0.4.1.tgz, r-release (x86_64): stepwedgepower_0.4.1.tgz, r-oldrel (x86_64): stepwedgepower_0.4.1.tgz
Old sources: stepwedgepower archive

Linking:

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