Analysis of Factorial Experiments
Methods for afex_aov objects
Set/get global afex options
m-way Plot with Error Bars and Raw Data
tools:::Rd_package_title("afex")
Convenient ANOVA estimation for factorial designs
Compare two vectors using various tests.
Deprecated functions
Expected values of mean squares for factorial designsImplements the Co...
p-values for fixed effects of mixed-model via lme4::lmer()
Make nice ANOVA table for printing.
Predict method for afex_aov objects
Objects exported from other packages
Extract Residuals and Fitted Values from afex_aov objects
Helper functions for rounding p-values
Set global contrasts
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).
Useful links