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Robust analysis of variance

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  • Herbert Buning

Abstract

For the c -sample location problem with equal and unequal variances, we compare the classical F -test and its robustified version-the Welch test-with some nonparametric counterparts defined for two-sided and one-sided ordered alternatives, such as trend and umbrella alternatives. A new rank test for long-tailed distributions is proposed. The comparison is referred to level alpha and power beta of the tests, and is carried out via Monte Carlo simulation, assuming short-, medium- and long-tailed as well as asymmetric distributions. It turns out that the Welch test is the best one in the case of unequal variances but in the case of equal variances special non-parametric tests are to prefer.

Suggested Citation

  • Herbert Buning, 1997. "Robust analysis of variance," Journal of Applied Statistics, Taylor & Francis Journals, vol. 24(3), pages 319-332.
    • Handle: RePEc:taf:japsta:v:24:y:1997:i:3:p:319-332
    DOI: 10.1080/02664769723710
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    Cited by:

    1. Fried, Roland & Gather, Ursula, 2006. "On rank tests for shift detection in time series," Technical Reports 2006,48, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    2. Herbert BUNing, 1999. "Adaptive Jonckheere-type tests for ordered alternatives," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(5), pages 541-551.

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