Simulation-Based Power Analysis for Mixed-Effects Models
Overview
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.
- Reduce overall
R CMD checktime well under CRAN's budget: vignettes now use small toy designs and few iterations, and the heavy simulation/correctness tests are markedskip_on_cran()(they still run in continuous integration and the lme4 path is exercised by examples). No user-facing changes.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 55 (2 internal)includes a package overview page
- Examples that run
- 56%10 run in a plain check · 8 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 35%
- Documented parameters
- 97%
- Return-value docs
- 96%
- Help pages citing references
- 2%
Downloads
Repository
Stars over time
Releases over time
12 development-tooling and community-health practices detected across 5 families in the upstream repository
Checks run against github.com/alitovchenko/mixpower on 2026-10-18.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
GitHub Pages site last deployed 2026-03-15 · The repository has a site deploy workflow
Show all practicesHide 1 practice
Dependencies
Code & Tests
Datasets
People & History
Maintainer since 0.1.0 (2026)
Pick two releases to compare their code metrics.
- 1.1.1Latest2026-06-25 · current release · diff ↗ ·
added 29 exports
mp_backend, mp_backend_glmmtmb, mp_beta_to_d, mp_beta_to_r2, mp_calibrate, mp_compare_models, mp_d_to_beta, mp_extend, mp_f_to_beta, mp_from_fit, mp_grid_sample_size, mp_icc_to_sd, mp_logodds_to_or, mp_methods_text, mp_missing, mp_or_to_logodds, mp_parallel_cluster, mp_power_checkpoint, mp_quick_power, mp_r2_to_beta, mp_recommend_method, mp_safeguard_effect, mp_scenario_glmmtmb_lmm, mp_sd_to_icc, mp_sensitivity_cell_run, mp_sensitivity_parallel, mp_sesoi, mp_t_to_beta, validate_mp_backend - RR 4.6.0 released · 2026-04-24
- 0.1.02026-02-12
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-02-12
- Total releases
- 2 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 4.1.0
- Download size
- 204 KB
Cite
Cite this package
Run in R for the authors' entry:
citation("mixpower")The package provides a citation file, so citation() returns the authors' own entry.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.