Overview

This following guides explore how to conduct various analysis of variance (ANOVA) tests in R with freely available packages. Focus is placed on demonstrating how to implement ANOVA tests in R rather than providing a conceptual background. To strengthen one’s background on ANOVA, I recommend picking up what’s been described as the ANOVA bible — Maxwell, Delaney, and Kelley’s 3rd edition of “Designing Experiments and Analyzing Data: A model comparison perspective”. For many of the guides, the accompanying R package for the Maxwell et al. text, will be used for sample data sets.

Requirements

• Working installation of RStudio & R
• Packages:
  • AMCP
  • jmv
  • rstatix
  • ggpubr
  • tidyverse

Topics covered

• One-way ANOVA

  Designs with one between-subjects factor.

• Welch's one-way ANOVA

  Designs with one between-subjects factor that fail to meet the homogeneity of variance assumption.

• Two-way ANOVA

  Designs with two between-subjects factors.

• One-way ANCOVA

  Designs with one between-subjects factor and one continuous covariate.

• One-way Repeated Measures ANOVA

  Designs with one within-subjects factor.

• Two-way Repeated Measures ANOVA

  Designs with two within-subjects factors.

• Mixed design ANOVA

  Designs with one between-subjects factor and one within-subjects factor.

• Continue