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
2011 Impact Factor: 1.877
2011 SCImago Journal Rankings: 0.248
DOIhttp://dx.doi.org/10.1002/sim.2486
ISI Accession Number IDWOS:000242429400006
ReferencesReferences in Scopus
DC Field
Value
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
2011 Impact Factor: 1.877
2011 SCImago Journal Rankings: 0.248
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
Author Affiliations
  1. Graduate University of Chinese Academy of Sciences
  2. The University of Hong Kong
  3. University of Amsterdam
  4. Imperial College London