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AnovaFun.jl

AnovaFun — Module
AnovaFun.jl

A Julia implementation of a traditional anova type analysis loosely based (inspired) by R's ez, afex, and emmeans packages. NB: This is not a full implementation (many features are missing!), but a simplified version implementing basic/standard anova functionality, and functionality that I currently use. IT IS PROBABLY (DEFINITELY!) MISSING SOMETHING (LOTS!) IMPORTANT!

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A Julia package for analysis of factorial experiments, including repeated measures (within-subjects), between-subjects, and mixed designs, inspired by the R packages afex, ez and emmeans.

Overview

AnovaFun.jl provides comprehensive ANOVA functionality for factorial experimental designs. The package implements traditional ANOVA methods with support for within-subjects (repeated measures), between-subjects, and mixed designs.

Note: This package implements a subset of features from R packages afex, ez, and emmeans, focusing on common ANOVA analyses. It has been tested against R's aov, ezANOVA, afex, emmeans, and JASP's ANOVA interface.

Features

  • Between-subjects ANOVA - Compare groups across independent subjects
  • Within-subjects (Repeated Measures) ANOVA - Compare conditions within the same subjects
  • Mixed-design ANOVA - Combine between and within factors
  • Estimated Marginal Means (emmeans) - Calculate marginal means with confidence intervals
  • Pairwise Comparisons - Post-hoc tests with multiple comparison adjustments
  • Sphericity Corrections - Greenhouse-Geisser and Huynh-Feldt corrections
  • Effect Sizes - η² (eta squared), partial η², and ω² (omega squared)
  • Interactive Plots - Publication-quality plots via Makie
  • APA-formatted Tables - PrettyTables integration for publication-ready output

Quick Start

using AnovaFun

# Load your data (long format, one row per observation)
# data = CSV.read("your_data.csv", DataFrame)

# Between-subjects ANOVA
result = anova(data, :dv, :subject, between = [:group])

# Within-subjects ANOVA
result = anova(data, :dv, :subject, within = [:time])

# Mixed design
result = anova(data, :dv, :subject, between = [:group], within = [:time])

# View results
result.table  # ANOVA table

# Estimated marginal means
em = emmeans(result)

# Interactive plots
plot_anova(em, x_grouping = :time, y_grouping = :group)

Installation

# From the Julia General Registry
using Pkg
Pkg.add("AnovaFun")

# Or directly from GitHub
Pkg.add(url="https://github.com/igmmgi/AnovaFun.jl")

Documentation