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Article: Semi-parametric accelerated failure time regression analysis with application to interval-censored HIV/AIDS data

TitleSemi-parametric accelerated failure time regression analysis with application to interval-censored HIV/AIDS data
Authors
KeywordsAsymptotically efficient
HIV
Interval-censored data
Partial linear model
Sieve maximum likelihood estimator
Issue Date2006
PublisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0277-6715/
Citation
Statistics In Medicine, 2006, v. 25 n. 22, p. 3850-3863 How to Cite?
AbstractThis paper demonstrates a way to investigate a potentially non-linear relationship between an interval-censored response variable and a continuously distributed explanatory variable. A potentially non-linear effect of a continuous explanatory variable on the response is incorporated into an accelerated failure time model, forming a partial linear model. A sieve maximum likelihood estimator (MLE) is suggested to simultaneously estimate all the parameters. The sieve MLE is shown to be asymptotically efficient and normally distributed. Simulation studies show that the proposed estimators for the scale and regression parameters are robust and efficient, and the estimator for the non-linear function is able to capture the shape of a variety of smooth non-linear functions. The model is applied to observational HIV data, where the response variable is the time to suppression of HIV viral load after initiation of antiretroviral therapy, and baseline viral load is investigated as a potentially non-linear effect. Copyright © 2005 John Wiley & Sons, Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/92606
ISSN
2023 Impact Factor: 1.8
2023 SCImago Journal Rankings: 1.348
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorXue, Hen_HK
dc.contributor.authorLam, KFen_HK
dc.contributor.authorCowling, BJen_HK
dc.contributor.authorde Wolf, Fen_HK
dc.date.accessioned2010-09-17T10:51:30Z-
dc.date.available2010-09-17T10:51:30Z-
dc.date.issued2006en_HK
dc.identifier.citationStatistics In Medicine, 2006, v. 25 n. 22, p. 3850-3863en_HK
dc.identifier.issn0277-6715en_HK
dc.identifier.urihttp://hdl.handle.net/10722/92606-
dc.description.abstractThis paper demonstrates a way to investigate a potentially non-linear relationship between an interval-censored response variable and a continuously distributed explanatory variable. A potentially non-linear effect of a continuous explanatory variable on the response is incorporated into an accelerated failure time model, forming a partial linear model. A sieve maximum likelihood estimator (MLE) is suggested to simultaneously estimate all the parameters. The sieve MLE is shown to be asymptotically efficient and normally distributed. Simulation studies show that the proposed estimators for the scale and regression parameters are robust and efficient, and the estimator for the non-linear function is able to capture the shape of a variety of smooth non-linear functions. The model is applied to observational HIV data, where the response variable is the time to suppression of HIV viral load after initiation of antiretroviral therapy, and baseline viral load is investigated as a potentially non-linear effect. Copyright © 2005 John Wiley & Sons, Ltd.en_HK
dc.languageengen_HK
dc.publisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0277-6715/en_HK
dc.relation.ispartofStatistics in Medicineen_HK
dc.rightsStatistics in Medicine. Copyright © John Wiley & Sons Ltd.-
dc.subjectAsymptotically efficienten_HK
dc.subjectHIV-
dc.subjectInterval-censored data-
dc.subjectPartial linear model-
dc.subjectSieve maximum likelihood estimator-
dc.subject.meshAnti-Retroviral Agents - therapeutic useen_HK
dc.subject.meshComputer Simulationen_HK
dc.subject.meshHIV - growth & developmenten_HK
dc.subject.meshHIV Infections - drug therapy - virologyen_HK
dc.subject.meshHumansen_HK
dc.subject.meshLikelihood Functionsen_HK
dc.subject.meshModels, Biologicalen_HK
dc.subject.meshNetherlandsen_HK
dc.subject.meshRegression Analysisen_HK
dc.subject.meshViral Loaden_HK
dc.titleSemi-parametric accelerated failure time regression analysis with application to interval-censored HIV/AIDS dataen_HK
dc.typeArticleen_HK
dc.identifier.emailLam, KF:hrntlkf@hkucc.hku.hken_HK
dc.identifier.emailCowling, BJ:bcowling@hku.hken_HK
dc.identifier.authorityLam, KF=rp00718en_HK
dc.identifier.authorityCowling, BJ=rp01326en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/sim.2486en_HK
dc.identifier.pmid16372386-
dc.identifier.scopuseid_2-s2.0-33750878541en_HK
dc.identifier.hkuros129196-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33750878541&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume25en_HK
dc.identifier.issue22en_HK
dc.identifier.spage3850en_HK
dc.identifier.epage3863en_HK
dc.identifier.eissn1097-0258-
dc.identifier.isiWOS:000242429400006-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridXue, H=7202517221en_HK
dc.identifier.scopusauthoridLam, KF=8948421200en_HK
dc.identifier.scopusauthoridCowling, BJ=8644765500en_HK
dc.identifier.scopusauthoridde Wolf, F=7005022848en_HK
dc.identifier.issnl0277-6715-

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