afex-package: Analysis of Factorial Experiments

In afex: Analysis of Factorial Experiments

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).

Details

The DESCRIPTION file: This package was not yet installed at build time.

Author(s)

Maintainer: Henrik Singmann [e-mail] (ORCID)

Authors:

• Ben Bolker

• Jake Westfall

• Frederik Aust (ORCID)

• Mattan S. Ben-Shachar

Other contributors:

• Søren Højsgaard [contributor]

• John Fox [contributor]

• Michael A. Lawrence [contributor]

• Ulf Mertens [contributor]

• Jonathon Love [contributor]

• Russell Lenth [contributor]

• Rune Haubo Bojesen Christensen [contributor]

See Also

Useful links:

• https://afex.singmann.science/

• https://github.com/singmann/afex

• Report bugs at https://github.com/singmann/afex/issues

afex documentation built on April 18, 2023, 1:09 a.m.