Rank tests for ANOVA with large number of factor levels

DSpace/Manakin Repository

Show simple item record

dc.contributor.author Wang, H en
dc.contributor.author Akritas, MG en
dc.date.accessioned 2014-03-01T02:49:54Z
dc.date.available 2014-03-01T02:49:54Z
dc.date.issued 2004 en
dc.identifier.issn 10485252 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/34771
dc.relation.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-2542510739&partnerID=40&md5=cd184c5442b3db77150eb4bc8774e6c1 en
dc.subject Large number of factor levels en
dc.subject Nonparametric en
dc.subject Projection method en
dc.subject Quadratic forms en
dc.subject Rank tests en
dc.subject Unbalanced designs en
dc.title Rank tests for ANOVA with large number of factor levels en
heal.type conferenceItem en
heal.publicationDate 2004 en
heal.abstract Recent papers (Boos, D. D and Brownie, C. (1995). ANOVA and rank tests when the number of treatments is large. Statist. Probab. Lett., 23, 183-191; Akritas, M. G. and Arnold, S. (2000). Asymptotics for ANOVA when the number of levels is large. Journal of the American Statistical Association, 95, 212-226; Bathke, A. (2002). ANOVA for a large number of treatments. Mathematical Methods of Statistics, 11(1), 118-132; Akritas and Papadatos 2004; Wang and Akritas 2003) have studied asymptotic properties of ANOVA F-statistics, under general distribution assumptions, when the number of levels is large. Most of these results pertain to statistics based on the original observations, which require strong moment assumptions and are sensitive to outliers. In this paper, we study the use of rank statistics as robust alternatives. Balanced and unbalanced, homoscedastic and heteroscedastic ANOVA models are considered. The main asymptotic tools are the asymptotic rank transform and Hájek's projection method. Simulation results show that the present rank statistics outperform those based on the original observations, in terms of both Type I and Type II errors. en
heal.journalName Journal of Nonparametric Statistics en
dc.identifier.volume 16 en
dc.identifier.issue 3-4 en
dc.identifier.spage 563 en
dc.identifier.epage 589 en

Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record