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Article: Model checking for additive hazards model with multivariate survival data

TitleModel checking for additive hazards model with multivariate survival data
Authors
KeywordsCumulative sum
Marginal model
Martingale residual
Multivariate failure time data
Parallel hazards
Score process
Issue Date2007
PublisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/jmva
Citation
Journal Of Multivariate Analysis, 2007, v. 98 n. 5, p. 1018-1032 How to Cite?
AbstractMultivariate failure time data often arise in biomedical studies due to natural or artificial clustering. With appropriate adjustment for the underlying correlation, the marginal additive hazards model characterizes the hazard difference via a linear link function between the hazard and covariates. We propose a class of graphical and numerical methods to assess the overall fitting adequacy of the marginal additive hazards model. The test statistics are based on the supremum of the stochastic processes derived from the cumulative sum of the martingale-based residuals over time and/or covariates. The distribution of the stochastic process can be approximated through a simulation technique. The proposed tests examine how unusual the observed stochastic process is, compared to a large number of realizations from the approximated process. This class of tests is very general and suitable for various purposes of model fitting evaluation. Simulation studies are conducted to examine the finite sample performance, and the model-checking methods are illustrated with data from an otitis media study. © 2006 Elsevier Inc. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/146580
ISSN
2015 Impact Factor: 0.857
2015 SCImago Journal Rankings: 1.458
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYin, Gen_HK
dc.date.accessioned2012-05-02T08:37:10Z-
dc.date.available2012-05-02T08:37:10Z-
dc.date.issued2007en_HK
dc.identifier.citationJournal Of Multivariate Analysis, 2007, v. 98 n. 5, p. 1018-1032en_HK
dc.identifier.issn0047-259Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/146580-
dc.description.abstractMultivariate failure time data often arise in biomedical studies due to natural or artificial clustering. With appropriate adjustment for the underlying correlation, the marginal additive hazards model characterizes the hazard difference via a linear link function between the hazard and covariates. We propose a class of graphical and numerical methods to assess the overall fitting adequacy of the marginal additive hazards model. The test statistics are based on the supremum of the stochastic processes derived from the cumulative sum of the martingale-based residuals over time and/or covariates. The distribution of the stochastic process can be approximated through a simulation technique. The proposed tests examine how unusual the observed stochastic process is, compared to a large number of realizations from the approximated process. This class of tests is very general and suitable for various purposes of model fitting evaluation. Simulation studies are conducted to examine the finite sample performance, and the model-checking methods are illustrated with data from an otitis media study. © 2006 Elsevier Inc. All rights reserved.en_HK
dc.languageengen_US
dc.publisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/jmvaen_HK
dc.relation.ispartofJournal of Multivariate Analysisen_HK
dc.subjectCumulative sumen_HK
dc.subjectMarginal modelen_HK
dc.subjectMartingale residualen_HK
dc.subjectMultivariate failure time dataen_HK
dc.subjectParallel hazardsen_HK
dc.subjectScore processen_HK
dc.titleModel checking for additive hazards model with multivariate survival dataen_HK
dc.typeArticleen_HK
dc.identifier.emailYin, G: gyin@hku.hken_HK
dc.identifier.authorityYin, G=rp00831en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1016/j.jmva.2006.02.005en_HK
dc.identifier.scopuseid_2-s2.0-33947145671en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33947145671&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume98en_HK
dc.identifier.issue5en_HK
dc.identifier.spage1018en_HK
dc.identifier.epage1032en_HK
dc.identifier.isiWOS:000246002900009-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridYin, G=8725807500en_HK

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