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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
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: PowRPriori_0.1.1.zip, r-release: not available, r-oldrel: PowRPriori_0.1.1.zip
macOS binaries: r-release (arm64): PowRPriori_0.1.1.tgz, r-oldrel (arm64): PowRPriori_0.1.1.tgz, r-release (x86_64): PowRPriori_0.1.1.tgz, r-oldrel (x86_64): PowRPriori_0.1.1.tgz

Linking:

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

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.