A1 Refereed original research article in a scientific journal
Weighted rank tests and Hodges-Lehmann estimates for the multivariate two-sample location problem with clustered data
Authors: Lemponen R, Larocque D, Nevalainen J, Oja H
Publisher: TAYLOR & FRANCIS LTD
Publication year: 2012
Journal: Journal of Nonparametric Statistics
Journal name in source: JOURNAL OF NONPARAMETRIC STATISTICS
Journal acronym: J NONPARAMETR STAT
Number in series: 4
Volume: 24
Issue: 4
First page : 977
Last page: 991
Number of pages: 15
ISSN: 1048-5252
DOI: https://doi.org/10.1080/10485252.2012.712693(external)
Abstract
A family of weighted rank tests and corresponding Hodges-Lehmann estimates are proposed for the analysis of multivariate two-sample clustered data. These procedures are a specific case of the nonparametric multivariate methods for clustered data considered by Nevalainen, Larocque, Oja, and Porsti [(2010), 'Nonparametric Analysis of Clustered Multivariate Data', Journal of the American Statistical Association, 105, 864-871]. This paper provides detailed proofs of their asymptotic properties that have not been previously published. Optimal weights for the procedures are derived and illustrated. The theoretical results are supplemented with simulation studies.
A family of weighted rank tests and corresponding Hodges-Lehmann estimates are proposed for the analysis of multivariate two-sample clustered data. These procedures are a specific case of the nonparametric multivariate methods for clustered data considered by Nevalainen, Larocque, Oja, and Porsti [(2010), 'Nonparametric Analysis of Clustered Multivariate Data', Journal of the American Statistical Association, 105, 864-871]. This paper provides detailed proofs of their asymptotic properties that have not been previously published. Optimal weights for the procedures are derived and illustrated. The theoretical results are supplemented with simulation studies.
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