etaSquared: Effect size for ANOVAs

Description

Calculates eta-squared and partial eta-squared effect sizes for an analysis of variance.

Usage

etaSquared(x, type = 2, anova = FALSE)

Value

A matrix with one row per term in the ANOVA model and columns for eta-squared (eta.sq) and partial eta-squared (eta.sq.part). If anova = TRUE, additional columns show the sums of squares, mean squares, degrees of freedom, F-statistics, and p-values.

Arguments

x: An aov object, as returned by aov.
type: Which type of sums of squares to use: 1 for Type I, 2 for Type II (the default), or 3 for Type III. Type II is recommended for most unbalanced designs.
anova: Set to TRUE to include the full ANOVA table alongside the effect sizes. Defaults to FALSE.

Details

Calculates eta-squared and partial eta-squared, two commonly used measures of effect size in analysis of variance. The input x should be an ANOVA fitted with aov.

For unbalanced designs, Type II sums of squares (type = 2) are recommended and are the default, consistent with the Anova function in the car package. Type I (type = 1) matches the output of anova but tests hypotheses that are often not of interest in unbalanced designs. Type III (type = 3) is also available.

Examples

Run this code

outcome <- c(1.4, 2.1, 3.0, 2.1, 3.2, 4.7, 3.5, 4.5, 5.4)
treatment1 <- factor(c(1, 1, 1, 2, 2, 2, 3, 3, 3))

# one-way ANOVA
anova1 <- aov(outcome ~ treatment1)
summary(anova1)
etaSquared(anova1)

# include the full ANOVA table
etaSquared(anova1, anova = TRUE)

# two-way ANOVA
treatment2 <- factor(c(1, 2, 3, 1, 2, 3, 1, 2, 3))
anova2 <- aov(outcome ~ treatment1 + treatment2)
etaSquared(anova2)