Analysis of Factorial Experiments
Description
Provides convenience functions for analyzing factorial experiments
using ANOVA or mixed models. ez.glm(), aov.car(), and aov4() allow
convenient 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), potentially aggregating multiple
observations per individual and cell of the design. mixed() fits a mixed
model using lme4::lmer() and computes p-values for all effects using either
Kenward-Roger 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). compare.2.vectors() compares two vectors using a variety of tests
(t, Wilcoxon, and permutation).