afex
Analysis of Factorial Experiments
Convenience functions for analyzing factorial experiments using ANOVA or mixed models. aov_ez(), aov_car(), and aov_4() allow specification of between, within (i.e., repeated-measures), or mixed (i.e., split-plot) ANOVAs for data in long format (i.e., one observation per row), automatically aggregating multiple observations per individual and cell of the design. mixed() fits mixed models using lme4::lmer() and computes p-values for all fixed effects using either Kenward-Roger or Satterthwaite approximation for degrees of freedom (LMM only), parametric bootstrap (LMMs and GLMMs), or likelihood ratio tests (LMMs and GLMMs). afex_plot() provides a high-level interface for interaction or one-way plots using ggplot2, combining raw data and model estimates. afex uses type 3 sums of squares as default (imitating commercial statistical software).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.5-1 |
2026-04-09 windows/windows R-4.5 | afex_1.5-1.zip |
3.5 MiB |
Dependencies (latest)
Depends
- lme4 (>= 1.1-8)
Imports
Suggests
- emmeans (>= 1.4)
- coin
- xtable
- parallel
- plyr
- optimx
- nloptr
- knitr
- rmarkdown
- R.rsp
- lattice
- latticeExtra
- multcomp
- testthat
- mlmRev
- dplyr
- tidyr
- dfoptim
- Matrix
- psychTools
- ggplot2
- MEMSS
- effects
- carData
- ggbeeswarm
- nlme
- cowplot
- jtools
- ggpubr
- MASS
- glmmTMB
- brms
- rstanarm
- statmod
- performance (>= 0.7.2)
- see (>= 0.6.4)
- ez
- ggResidpanel
- grid
- vdiffr
- GLMMadaptive
- ggthemes