Please use this identifier to cite or link to this item: https://doi.org/10.1111/j.1467-9876.2009.00702.x
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dc.titleInterval-censored data with repeated measurements and a cured subgroup
dc.contributor.authorLi, J.
dc.contributor.authorMa, S.
dc.date.accessioned2014-10-28T05:12:46Z
dc.date.available2014-10-28T05:12:46Z
dc.date.issued2010-08
dc.identifier.citationLi, J.,Ma, S. (2010-08). Interval-censored data with repeated measurements and a cured subgroup. Journal of the Royal Statistical Society. Series C: Applied Statistics 59 (4) : 693-705. ScholarBank@NUS Repository. <a href="https://doi.org/10.1111/j.1467-9876.2009.00702.x" target="_blank">https://doi.org/10.1111/j.1467-9876.2009.00702.x</a>
dc.identifier.issn00359254
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/105186
dc.description.abstractSummary: The hypobaric decompression sickness data study was conducted by the National Aeronautics and Space Administration to investigate the risk of decompression sickness in hypobaric environments. The quantity of interest is the time to onset of grade IV venous gas emboli, which was mixed case interval censored because of measurement limitations. In the study, some subjects participated in multiple experiments, leading to repeated and correlated measurements on those subjects. In addition, it has been suggested that some subjects had a much lower risk of developing grade IV venous gas emboli than others, i.e. those subjects were immune from the event of interest (or 'cured'). We propose to use two-part models, where the first part describes the probability of cure and the second part describes the survival for susceptible subjects. We use two random effects to account for the correlated nature of measurements. A leverage bootstrap approach is proposed for model diagnosis. A simulation study shows satisfactory performance of the estimation and diagnosis approaches proposed. Model estimation and evaluation of the hypobaric decompression sickness data are carefully investigated. © 2010 Royal Statistical Society.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1111/j.1467-9876.2009.00702.x
dc.sourceScopus
dc.subjectCure model
dc.subjectInterval censoring
dc.subjectTwo-part model
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1111/j.1467-9876.2009.00702.x
dc.description.sourcetitleJournal of the Royal Statistical Society. Series C: Applied Statistics
dc.description.volume59
dc.description.issue4
dc.description.page693-705
dc.identifier.isiutNOT_IN_WOS
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