Analysis of Factorial Experiments
Description
Provides convenience functions for analyzing factorial experiments
using ANOVA or mixed models. ez.glm(), aov.car(), or 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) aggregating more then one observation per
individual and cell of the design. mixed() fits a mixed model using
lme4::lmer() and computes p-values for all effects in the model using
either Kenward-Roger approximation of 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).