Analysis of Factorial Experiments
Description
Provides convenience functions for analyzing factorial
experiments using ANOVA or mixed-models. ez.glm() and aov.car()
allow convenient calculation of between, within (i.e.,
repeated-measures), or mixed between-within (i.e., split-plot)
ANOVAs for data in the long format (i.e., one observation per
row) wrapping car::Anova() (aggregating more then one
observation per individual and cell of the design), per default
returning a print ready ANOVA table. Function mixed() fits a
mixed model using lme4::lmer() and computes p-values for all
effects in the model using either the Kenward-Rogers
approximation of degrees of freedom (LMM only) or parametric
bootstrap (LMMs and GLMMs). afex uses type 3 sums of squares as
default (imitating commercial statistical software) and sets
the default contrasts to contr.sum. Furthermore,
compare.2.vectors() conveniently compares two vectors using
different statistical tests.