A1 Refereed original research article in a scientific journal
A weighted multivariate signed-rank test for cluster-correlated data
Authors: Haataja R, Larocque D, Nevalainen J, Oja H
Publisher: ELSEVIER INC
Publication year: 2009
Journal:: Journal of Multivariate Analysis
Journal name in source: JOURNAL OF MULTIVARIATE ANALYSIS
Journal acronym: J MULTIVARIATE ANAL
Volume: 100
Issue: 6
First page : 1107
Last page: 1119
Number of pages: 13
ISSN: 0047-259X
DOI: https://doi.org/10.1016/j.jmva.2008.10.009
Abstract
A weighted multivariate signed-rank test is introduced for an analysis of multivariate clustered data. Observations in different clusters may then get different weights. The test provides a robust and efficient alternative to normal theory based methods. Asymptotic theory is developed to find the approximate p-value as well as to calculate the limiting Pitman efficiency of the test. A conditionally distribution-free version of the test is also discussed. The finite-sample behavior of different versions of the test statistic is explored by simulations and the new test is compared to the unweighted and weighted versions of Hotelling's T(2) test and the multivariate spatial sign test introduced in [ D. Larocque, J. Nevalainen, H. Oja, A weighted multivariate sign test for cluster-correlated data, Biometrika 94 (2007) 267-283]. Finally, a real data example is used to illustrate the theory. (C) 2008 Elsevier Inc. All rights reserved.
A weighted multivariate signed-rank test is introduced for an analysis of multivariate clustered data. Observations in different clusters may then get different weights. The test provides a robust and efficient alternative to normal theory based methods. Asymptotic theory is developed to find the approximate p-value as well as to calculate the limiting Pitman efficiency of the test. A conditionally distribution-free version of the test is also discussed. The finite-sample behavior of different versions of the test statistic is explored by simulations and the new test is compared to the unweighted and weighted versions of Hotelling's T(2) test and the multivariate spatial sign test introduced in [ D. Larocque, J. Nevalainen, H. Oja, A weighted multivariate sign test for cluster-correlated data, Biometrika 94 (2007) 267-283]. Finally, a real data example is used to illustrate the theory. (C) 2008 Elsevier Inc. All rights reserved.
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