Improved tests for homogeneity of variances

Equality of variances is one of the key assumptions of analysis of variances (ANOVA). There are several testing procedures available to validate this assumption, but it is rare to find a test procedure which controls the type I error rate while providing high statistical power. In this article, we i...

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Bibliographic Details
Published in:	Communications in statistics. Simulation and computation Vol. 46; no. 9; pp. 7423 - 7446
Main Authors:	Jayalath, Kalanka P., Ng, Hon Keung Tony, Manage, Ananda B., Riggs, Kent E.
Format:	Journal Article
Language:	English
Published:	Philadelphia Taylor & Francis 21-10-2017 Taylor & Francis Ltd
Subjects:	Analysis of Variance Bartlett's Test Bootstrapping Equality of Variance Homogeneity Levene's Test Mean Absolute Deviance Primary 62G10 Regression analysis RMD Test Robust F-test Secondary 64F40 Statistical analysis Test procedures Two-stage Test
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Summary:	Equality of variances is one of the key assumptions of analysis of variances (ANOVA). There are several testing procedures available to validate this assumption, but it is rare to find a test procedure which controls the type I error rate while providing high statistical power. In this article, we introduce a bootstrap test based on the ratio of mean absolute deviances (RMD). We also propose a two-stage testing procedure where we first quantify the skewness of the distributions and then choose an appropriate test for homogeneity of variances. The performances of these test procedures are studied via a simulation study.
ISSN:	0361-0918 1532-4141
DOI:	10.1080/03610918.2016.1241404