A1 Refereed original research article in a scientific journal
Two sample tests for the nonparametric Behrens-Fisher problem with clustered data
Authors: Larocque D, Haataja R, Nevalainen J, Oja H
Publisher: TAYLOR & FRANCIS LTD
Publication year: 2010
Journal: Journal of Nonparametric Statistics
Journal name in source: JOURNAL OF NONPARAMETRIC STATISTICS
Journal acronym: J NONPARAMETR STAT
Article number: PII 918893090
Number in series: 6
Volume: 22
Issue: 6
First page : 755
Last page: 771
Number of pages: 17
ISSN: 1048-5252
DOI: https://doi.org/10.1080/10485250903469728
Abstract
In this paper, we consider the nonparametric Behrens-Fisher problem with cluster-correlated data. A class of weighted Mann-Whitney test statistics is introduced and studied. In particular, a comparison with other recent testing procedures for related problems is provided. The new tests are valid when the distributions do not have the same scales and/or shapes under the null hypothesis. A general class of weighted U-statistics for clustered data, encompassing the Mann-Whitney statistic, is also introduced. A simulation studies the type I error robustness and the power of the new and of some recently proposed procedures. This study shows that the incorporation of appropriate weights can greatly improve the power of the test. A real data example illustrates the use of the tests.
In this paper, we consider the nonparametric Behrens-Fisher problem with cluster-correlated data. A class of weighted Mann-Whitney test statistics is introduced and studied. In particular, a comparison with other recent testing procedures for related problems is provided. The new tests are valid when the distributions do not have the same scales and/or shapes under the null hypothesis. A general class of weighted U-statistics for clustered data, encompassing the Mann-Whitney statistic, is also introduced. A simulation studies the type I error robustness and the power of the new and of some recently proposed procedures. This study shows that the incorporation of appropriate weights can greatly improve the power of the test. A real data example illustrates the use of the tests.
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