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Weighted rank tests and Hodges-Lehmann estimates for the multivariate two-sample location problem with clustered data

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  • Riina Lemponen
  • Denis Larocque
  • Jaakko Nevalainen
  • Hannu Oja

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 Pörsti [(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.

Suggested Citation

  • Riina Lemponen & Denis Larocque & Jaakko Nevalainen & Hannu Oja, 2012. "Weighted rank tests and Hodges-Lehmann estimates for the multivariate two-sample location problem with clustered data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(4), pages 977-991, December.
    • Handle: RePEc:taf:gnstxx:v:24:y:2012:i:4:p:977-991
    DOI: 10.1080/10485252.2012.712693
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    References listed on IDEAS

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    1. Gerard, Patrick D. & Schucany, William R., 2007. "An enhanced sign test for dependent binary data with small numbers of clusters," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4622-4632, May.
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