PowRPriori: Power Analysis via Data Simulation for (Generalized) Linear Mixed Effects Models

Conduct a priori power analyses via Monte-Carlo style data simulation for linear and generalized linear mixed-effects models (LMMs/GLMMs). Provides a user-friendly workflow with helper functions to easily define fixed and random effects as well as diagnostic functions to evaluate the adequacy of the results of the power analysis.

Version: 0.1.1
Depends: R (≥ 3.5.0)
Imports: dplyr, doFuture, foreach, future, ggplot2, lme4, lmerTest, magrittr, MASS, purrr, rlang, scales, stats, tidyr, tidyselect, utils, tibble
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2025-12-14
DOI: 10.32614/CRAN.package.PowRPriori (may not be active yet)
Author: Markus Grill [aut, cre]
Maintainer: Markus Grill <markus.grill at uni-wh.de>
BugReports: https://github.com/mirgll/PowRPriori/issues
License: MIT + file LICENSE
URL: https://github.com/mirgll/PowRPriori
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: PowRPriori results

Documentation:

Reference manual: PowRPriori.html , PowRPriori.pdf
Vignettes: Complete Workflow with PowRPriori (source, R code)

Downloads:

Package source: PowRPriori_0.1.1.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): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

Please use the canonical form https://CRAN.R-project.org/package=PowRPriori to link to this page.