A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Weighted rank tests and Hodges-Lehmann estimates for the multivariate two-sample location problem with clustered data
Tekijät: Lemponen R, Larocque D, Nevalainen J, Oja H
Kustantaja: TAYLOR & FRANCIS LTD
Julkaisuvuosi: 2012
Journal: Journal of Nonparametric Statistics
Tietokannassa oleva lehden nimi: JOURNAL OF NONPARAMETRIC STATISTICS
Lehden akronyymi: J NONPARAMETR STAT
Numero sarjassa: 4
Vuosikerta: 24
Numero: 4
Aloitussivu: 977
Lopetussivu: 991
Sivujen määrä: 15
ISSN: 1048-5252
DOI: https://doi.org/10.1080/10485252.2012.712693
Tiivistelmä
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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