Analysis of Factorial Experiments
Released May 25, 2017 by Henrik Singmann [aut, cre], Ben Bolker [aut], Jake Westfall [aut], Frederik Aust [aut], Søren Højsgaard [ctb], John Fox [ctb], Michael A. Lawrence [ctb], Ulf Mertens [ctb], Jonathan Love [ctb]
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 between-within (i.e., split-plot) ANOVAs for data in long format (i.e., one observation per row), 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 uses type 3 sums of squares as default (imitating commercial statistical software).