Nonparametric models and methods for designs with dependent censored data: Part II

O'Gorman, JT; Akritas, MG

dc.contributor.author	O'Gorman, JT	en
dc.contributor.author	Akritas, MG	en
dc.date.accessioned	2014-03-01T02:49:50Z
dc.date.available	2014-03-01T02:49:50Z
dc.date.issued	2004	en
dc.identifier.issn	10485252	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34756
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-2542539771&partnerID=40&md5=75b715ece64aea3dc13e244e95ffba83	en
dc.subject	Correlated survival data	en
dc.subject	H-class statistics	en
dc.subject	Kaplan-Meier estimator	en
dc.subject	Martingales for counting process	en
dc.subject	Nonparametric hypotheses	en
dc.subject	Rank test	en
dc.title	Nonparametric models and methods for designs with dependent censored data: Part II	en
heal.type	conferenceItem	en
heal.publicationDate	2004	en
heal.abstract	We consider a fully nonparametric marginal model for the analysis of mixed models with censored data. Hypotheses in this context are formulated by decomposing the set of (marginal) distributions as introduced in Akritas and Arnold [Akritas, M. G. and Arnold, S. F. (1994). Fully nonparametric hypotheses for factorial designs I: Multivariate repeated measures designs. The Journal of the American Statistical Association, 89, 336-343]. The approach should be useful in cases where the assumptions of the proportional hazards or location shift models fail to be satisfied. The large sample distribution of the test statistics is based on a representation for Kaplan-Meier integrals. The methodology is illustrated with two real life examples using clustered data. These results generalize the results of O'Gorman and Akritas [O'Gorman, J. T. and Akritas, M. G. (2001). Nonparametric models and methods for designs with dependent censored data: Part I. Biometrics, 57, 88-95] for the case of repeated measures data.	en
heal.journalName	Journal of Nonparametric Statistics	en
dc.identifier.volume	16	en
dc.identifier.issue	3-4	en
dc.identifier.spage	613	en
dc.identifier.epage	622	en