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Two non-parametric, analysis-of-means-type tests for homogeneity of variances

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  • Peter Wludyka

Abstract

After a brief review of the literature, two non-parametric tests for homogeneity of variances are presented. The first test is based on the analysis of means for ranks, which is a non-parametric version of the analysis of means (ANOM) that uses ranks as input for an ANOM test. The second test uses inverse normal scores of the ranks of scale transformations of the observations as input to the ANOM. Both homogeneity of variances tests can be presented in a graphical form, which makes it easy for practitioners to assess the practical and the statistical significance. A Monte Carlo study is used to show that these tests have power comparable with that of well-known robust tests for homogeneity of variances.

Suggested Citation

  • Peter Wludyka, 1999. "Two non-parametric, analysis-of-means-type tests for homogeneity of variances," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(2), pages 243-256.
    • Handle: RePEc:taf:japsta:v:26:y:1999:i:2:p:243-256
    DOI: 10.1080/02664769922584
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    References listed on IDEAS

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    1. Allen Fleishman, 1978. "A method for simulating non-normal distributions," Psychometrika, Springer;The Psychometric Society, vol. 43(4), pages 521-532, December.
    2. John Overall & J. Arthur Woodward, 1974. "A simple test for heterogeneity of variance in complex factorial designs," Psychometrika, Springer;The Psychometric Society, vol. 39(3), pages 311-318, September.
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    Cited by:

    1. Philip Pallmann & Ludwig A. Hothorn, 2016. "Analysis of means: a generalized approach using R," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(8), pages 1541-1560, June.

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