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

Riina Lemponen, Denis Larocque, Jaakko Nevalainen and Hannu Oja

Journal of Nonparametric Statistics, 2012, vol. 24, issue 4, 977-991

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.

Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10485252.2012.712693 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gnstxx:v:24:y:2012:i:4:p:977-991

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GNST20

DOI: 10.1080/10485252.2012.712693

Access Statistics for this article

Journal of Nonparametric Statistics is currently edited by Jun Shao

More articles in Journal of Nonparametric Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().