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mixpower  

Simulation-Based Power Analysis for Mixed-Effects Models
View on CRAN: Click here


Download and install mixpower package within the R console
Install from CRAN:
install.packages("mixpower")

Install from Github:
library("remotes")
install_github("cran/mixpower")

Install by package version:
library("remotes")
install_version("mixpower", "1.1.1")



Attach the package and use:
library("mixpower")
Maintained by
Mixpower Alex Litovchenko
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-02-12
Latest Update: 2026-02-12
Description:
A comprehensive, simulation-based toolkit for power and sample-size analysis for linear and generalized linear mixed-effects models (LMMs and GLMMs). Supports Gaussian, binomial, Poisson, and negative binomial families via 'lme4'; Wald and likelihood-ratio tests; multi-parameter sensitivity grids; power curves and minimum sample-size solvers; parallel evaluation with deterministic seeds; and full reproducibility (manifests, result bundling, and export to CSV/JSON). Delivers thorough diagnostics per run (failure rate, singular-fit rate, effective N) and publication-ready summary tables. References: Bates et al. (2015) "Fitting Linear Mixed-Effects Models Using lme4" <doi:10.18637/jss.v067.i01>; Green and MacLeod (2016) "SIMR: an R package for power analysis of generalized linear mixed models by simulation" <doi:10.1111/2041-210X.12504>.
How to cite:
Mixpower Alex Litovchenko (2026). mixpower: Simulation-Based Power Analysis for Mixed-Effects Models. R package version 1.1.1, https://cran.r-project.org/web/packages/mixpower. Accessed 25 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:31), 0.1.0 (2026-02-12 09:20)
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Functions, R codes and Examples using the mixpower R package
Full mixpower package functions and examples
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