afex
Analysis of Factorial Experiments
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).
- Version1.4-1
- R version≥ 3.5.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release09/01/2024
Documentation
- VignetteAnalysis of Accuracy Data using ANOVA and binomial GLMMs
- VignetteANOVA and Post-Hoc Contrasts: Reanalysis of Singmann and Klauer (2011)
- VignetteMixed Model Example Analysis: Reanalysis of Freeman et al. (2010)
- Vignetteafex_plot: Publication Ready Plots for Experimental Designs
- Vignetteafex_plot: Supported Models
- VignetteTesting the Assumptions of ANOVAs
- VignetteAn Introduction to Mixed Models for Experimental Psychology
- MaterialREADME
- MaterialNEWS
- In ViewsMixedModels
Team
Henrik Singmann
Ben Bolker
John Fox
Søren Højsgaard
Show author detailsRolesContributorMattan S. Ben-Shachar
Russell Lenth
Show author detailsRolesContributorMichael A. Lawrence
Show author detailsRolesContributorJonathon Love
Show author detailsRolesContributorRune Haubo Bojesen Christensen
Show author detailsRolesContributorFrederik Aust
Jake Westfall
Show author detailsRolesAuthorUlf Mertens
Show author detailsRolesContributor
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