Compute (classic, full) omega-squared and partial omega-squared for all terms in a between-subjects ANOVA model. Omega squared is a less-biased alternative to eta squared, estimating the population effect size rather than the sample one.
See the Datanovia tutorial One-Way ANOVA in R for a worked walkthrough.
omega_squared(model)
partial_omega_squared(model)an object of class aov or anova (a between-subjects
design). Repeated-measures and mixed models are not supported, as for
eta_squared().
a named numeric vector of effect sizes, one per model term. A negative point estimate (which can arise for a term with F < 1) is floored at 0, since omega squared estimates a non-negative proportion of variance.
omega_squared(): compute the classic (full) omega squared.
partial_omega_squared(): compute partial omega squared.
Olejnik, S., & Algina, J. (2003). Generalized eta and omega squared statistics: Measures of effect size for some common research designs. Psychological Methods, 8(4), 434-447.
eta_squared(), anova_test().
The Datanovia tutorial: One-Way ANOVA in R.
# Data preparation
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Fit the model
res.aov <- aov(len ~ supp * dose, data = df)
# Effect size
omega_squared(res.aov)
#> supp dose supp:dose
#> 0.05545191 0.69257877 0.02364656
partial_omega_squared(res.aov)
#> supp dose supp:dose
#> 0.19540824 0.75206604 0.09384698