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A closer examination on some parametric alternatives to the ANOVA F-test

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Abstract

In experiments, the classical (ANOVA) F-test is often used to test the omnibus null-hypothesis μ1 = μ2 ... = μ j = ... = μ n (all n population means are equal) in a one-way ANOVA design, even when one or more basic assumptions are being violated. In the first part of this article, we will briefly discuss the consequences of the different types of violations of the basic assumptions (dependent measurements, non-normality, heteroscedasticity) on the validity of the F-test. Secondly, we will present a simulation experiment, designed to compare the type I-error and power properties of both the F-test and some of its parametric adaptations: the Brown & Forsythe F*-test and Welch’s Vw-test. It is concluded that the Welch Vw-test offers acceptable control over the type I-error rate in combination with (very) high power in most of the experimental conditions. Therefore, its use is highly recommended when one or more basic assumptions are being violated. In general, the use of the Brown & Forsythe F*-test cannot be recommended on power considerations unless the design is balanced and the homoscedasticity assumption holds.

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  1. Faculty of Applied Economics Computer Science and Operations Management, University of Antwerp-RUCA, Middelheimlaan 1, B-2020, Antwerpen, Belgium

    A. De Beuckelaer

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De Beuckelaer, A. A closer examination on some parametric alternatives to the ANOVA F-test. Statistical Papers 37, 291–305 (1996). https://doi.org/10.1007/BF02926110

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  • DOI: https://doi.org/10.1007/BF02926110

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