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Article: Semi-parametric accelerated failure time regression analysis with application to interval-censored HIV/AIDS data
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TitleSemi-parametric accelerated failure time regression analysis with application to interval-censored HIV/AIDS data
 
AuthorsXue, H1
Lam, KF2
Cowling, BJ4
de Wolf, F3
 
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/
 
CitationStatistics In Medicine, 2006, v. 25 n. 22, p. 3850-3863 [How to Cite?]
DOI: http://dx.doi.org/10.1002/sim.2486
 
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.
 
ISSN0277-6715
2012 Impact Factor: 2.044
2012 SCImago Journal Rankings: 1.691
 
DOIhttp://dx.doi.org/10.1002/sim.2486
 
ISI Accession Number IDWOS:000242429400006
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorXue, H
 
dc.contributor.authorLam, KF
 
dc.contributor.authorCowling, BJ
 
dc.contributor.authorde Wolf, F
 
dc.date.accessioned2010-09-17T10:51:30Z
 
dc.date.available2010-09-17T10:51:30Z
 
dc.date.issued2006
 
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.
 
dc.description.naturelink_to_subscribed_fulltext
 
dc.identifier.citationStatistics In Medicine, 2006, v. 25 n. 22, p. 3850-3863 [How to Cite?]
DOI: http://dx.doi.org/10.1002/sim.2486
 
dc.identifier.doihttp://dx.doi.org/10.1002/sim.2486
 
dc.identifier.eissn1097-0258
 
dc.identifier.epage3863
 
dc.identifier.hkuros129196
 
dc.identifier.isiWOS:000242429400006
 
dc.identifier.issn0277-6715
2012 Impact Factor: 2.044
2012 SCImago Journal Rankings: 1.691
 
dc.identifier.issue22
 
dc.identifier.pmid16372386
 
dc.identifier.scopuseid_2-s2.0-33750878541
 
dc.identifier.spage3850
 
dc.identifier.urihttp://hdl.handle.net/10722/92606
 
dc.identifier.volume25
 
dc.languageeng
 
dc.publisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0277-6715/
 
dc.publisher.placeUnited Kingdom
 
dc.relation.ispartofStatistics in Medicine
 
dc.relation.referencesReferences in Scopus
 
dc.rightsStatistics in Medicine. Copyright © John Wiley & Sons Ltd.
 
dc.subject.meshAnti-Retroviral Agents - therapeutic use
 
dc.subject.meshComputer Simulation
 
dc.subject.meshHIV - growth & development
 
dc.subject.meshHIV Infections - drug therapy - virology
 
dc.subject.meshHumans
 
dc.subject.meshLikelihood Functions
 
dc.subject.meshModels, Biological
 
dc.subject.meshNetherlands
 
dc.subject.meshRegression Analysis
 
dc.subject.meshViral Load
 
dc.subjectAsymptotically efficient
 
dc.subjectHIV
 
dc.subjectInterval-censored data
 
dc.subjectPartial linear model
 
dc.subjectSieve maximum likelihood estimator
 
dc.titleSemi-parametric accelerated failure time regression analysis with application to interval-censored HIV/AIDS data
 
dc.typeArticle
 
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Author Affiliations
  1. Graduate University of Chinese Academy of Sciences
  2. The University of Hong Kong
  3. University of Amsterdam
  4. Imperial College London