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Article: A second‐order semiparametric method for survival analysis, with application to an acquired immune deficiency syndrome clinical trial study

TitleA second‐order semiparametric method for survival analysis, with application to an acquired immune deficiency syndrome clinical trial study
Authors
KeywordsCD4 cell counts
Censoring
Efficiency
Imputation
Kernel
Non-parametric methods
Restricted moments
Safety end points
Toxicity
Two-stage analysis
Issue Date2016
PublisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/RSSC
Citation
Journal of the Royal Statistical Society. Series C: Applied Statistics, 2016 How to Cite?
AbstractMotivated by the recent acquired immune deficiency syndrome clinical trial study A5175, we propose a semiparametric framework to describe time-to-event data, where only the dependence of the mean and variance of the time on the covariates are specified through a restricted moment model. We use a second-order semiparametric efficient score combined with a non-parametric imputation device for estimation. Compared with an imputed weighted least squares method, the approach proposed improves the efficiency of the parameter estimation whenever the third moment of the error distribution is non-zero. We compare the method with a parametric survival regression method in the A5175 study data analysis. In the data analysis, the method proposed shows a better fit to the data with smaller mean-squared residuals. In summary, this work provides a semiparametric framework in modelling and estimation of survival data. The framework has wide applications in data analysis.
Persistent Identifierhttp://hdl.handle.net/10722/236344
ISSN
2023 Impact Factor: 1.0
2023 SCImago Journal Rankings: 0.739
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorJiang, F-
dc.contributor.authorMa, Y-
dc.contributor.authorJack Lee, J-
dc.date.accessioned2016-11-24T01:18:56Z-
dc.date.available2016-11-24T01:18:56Z-
dc.date.issued2016-
dc.identifier.citationJournal of the Royal Statistical Society. Series C: Applied Statistics, 2016-
dc.identifier.issn0035-9254-
dc.identifier.urihttp://hdl.handle.net/10722/236344-
dc.description.abstractMotivated by the recent acquired immune deficiency syndrome clinical trial study A5175, we propose a semiparametric framework to describe time-to-event data, where only the dependence of the mean and variance of the time on the covariates are specified through a restricted moment model. We use a second-order semiparametric efficient score combined with a non-parametric imputation device for estimation. Compared with an imputed weighted least squares method, the approach proposed improves the efficiency of the parameter estimation whenever the third moment of the error distribution is non-zero. We compare the method with a parametric survival regression method in the A5175 study data analysis. In the data analysis, the method proposed shows a better fit to the data with smaller mean-squared residuals. In summary, this work provides a semiparametric framework in modelling and estimation of survival data. The framework has wide applications in data analysis.-
dc.languageeng-
dc.publisherWiley-Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/RSSC-
dc.relation.ispartofJournal of the Royal Statistical Society. Series C: Applied Statistics-
dc.rightsPreprint This is the pre-peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article]. Authors are not required to remove preprints posted prior to acceptance of the submitted version. Postprint This is the accepted version of the following article: [full citation], which has been published in final form at [Link to final article].-
dc.subjectCD4 cell counts-
dc.subjectCensoring-
dc.subjectEfficiency-
dc.subjectImputation-
dc.subjectKernel-
dc.subjectNon-parametric methods-
dc.subjectRestricted moments-
dc.subjectSafety end points-
dc.subjectToxicity-
dc.subjectTwo-stage analysis-
dc.titleA second‐order semiparametric method for survival analysis, with application to an acquired immune deficiency syndrome clinical trial study-
dc.typeArticle-
dc.identifier.emailJiang, F: feijiang@hku.hk-
dc.identifier.authorityJiang, F=rp02185-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/rssc.12189-
dc.identifier.scopuseid_2-s2.0-84995632256-
dc.identifier.isiWOS:000405101800009-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl0035-9254-

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