Analysis of Factorial Experiments
Description
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).