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Open Access Research Article

ANOVA F-test and Kruskal-Wallis test performance comparison under varying distributions, variance heterogeneity, sample sizes, and noncentrality structures

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* Corresponding author · click or hover a name for details

pp. 1595–1613Vol. 27Issue 8November 2024DOI: 10.47974/JSMS-1116XML
Received:
14 Dec 2022
Published Online:
18 Dec 2024
Article type:
Research Article
Language:
EN
Article no.:
JSMS-1116
Pages:
1595–1613

Abstract

This study provides a direct comparison of the ANOVA F-test and the Kruskal-Wallis Test, a commonly used nonparametric alternative, in terms of type I error rate and power performance. The Monte Carlo simulation expands upon previous studies by varying all common relevant factors simultaneously. The study included normal and nonnormal distributions, homogeneous and heterogeneous variance structures, balanced and unbalanced sample size designs, and also four specific noncentrality structures. Results indicate that the Kruskal-Wallis test is optimal to its parametric counterpart in many specific types of configurations.

Keywords

Subject Classifications

62G10 - Nonparametric Hypothesis Testing

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