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Article: A marginal likelihood approach to estimation in frailty models

TitleA marginal likelihood approach to estimation in frailty models
Authors
KeywordsCensoring
Importance sampling
Laplace transform
Monte Carlo method
Issue Date1997
PublisherAmerican Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main
Citation
Journal Of The American Statistical Association, 1997, v. 92 n. 439, p. 985-990 How to Cite?
AbstractA marginal likelihood approach is proposed for estimating the parameters in a frailty model using clustered survival data. To overcome the analytic intractability of the marginal likelihood function, we propose a Monte Carlo approximation using the technique of importance sampling. Implementation is by means of simulations from the uniform distribution. The suggested method can cope with censoring and unequal cluster sizes and can be applied to any frailty distribution with explicit Laplace transform. We concentrate on a two-parameter family that includes the gamma, inverse Gaussian, and posilive stable distributions as special cases. The method is illustrated using data from an animal carcinogenesis experiment and validated in a simulation study.
Persistent Identifierhttp://hdl.handle.net/10722/82939
ISSN
2015 Impact Factor: 1.725
2015 SCImago Journal Rankings: 3.447
References

 

DC FieldValueLanguage
dc.contributor.authorLam, KFen_HK
dc.contributor.authorKuk, AYCen_HK
dc.date.accessioned2010-09-06T08:35:07Z-
dc.date.available2010-09-06T08:35:07Z-
dc.date.issued1997en_HK
dc.identifier.citationJournal Of The American Statistical Association, 1997, v. 92 n. 439, p. 985-990en_HK
dc.identifier.issn0162-1459en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82939-
dc.description.abstractA marginal likelihood approach is proposed for estimating the parameters in a frailty model using clustered survival data. To overcome the analytic intractability of the marginal likelihood function, we propose a Monte Carlo approximation using the technique of importance sampling. Implementation is by means of simulations from the uniform distribution. The suggested method can cope with censoring and unequal cluster sizes and can be applied to any frailty distribution with explicit Laplace transform. We concentrate on a two-parameter family that includes the gamma, inverse Gaussian, and posilive stable distributions as special cases. The method is illustrated using data from an animal carcinogenesis experiment and validated in a simulation study.en_HK
dc.languageengen_HK
dc.publisherAmerican Statistical Association. The Journal's web site is located at http://www.amstat.org/publications/jasa/index.cfm?fuseaction=mainen_HK
dc.relation.ispartofJournal of the American Statistical Associationen_HK
dc.subjectCensoringen_HK
dc.subjectImportance samplingen_HK
dc.subjectLaplace transformen_HK
dc.subjectMonte Carlo methoden_HK
dc.titleA marginal likelihood approach to estimation in frailty modelsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0162-1459&volume=92&issue=439&spage=985&epage=990&date=1997&atitle=A+marginal+likelihood+approach+to+estimation+in+frailty+modelsen_HK
dc.identifier.emailLam, KF: hrntlkf@hkucc.hku.hken_HK
dc.identifier.authorityLam, KF=rp00718en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.2307/2965562-
dc.identifier.scopuseid_2-s2.0-21744450667en_HK
dc.identifier.hkuros28860en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-21744450667&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume92en_HK
dc.identifier.issue439en_HK
dc.identifier.spage985en_HK
dc.identifier.epage990en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLam, KF=8948421200en_HK
dc.identifier.scopusauthoridKuk, AYC=6701324431en_HK

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