Please use this identifier to cite or link to this item: https://doi.org/10.1002/sim.6093
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dc.titleEstimation of intervention effects using recurrent event time data in the presence of event dependence and a cured fraction
dc.contributor.authorXu, Y.
dc.contributor.authorLam, K.F.
dc.contributor.authorCheung, Y.B.
dc.date.accessioned2014-11-26T08:28:09Z
dc.date.available2014-11-26T08:28:09Z
dc.date.issued2014-06-15
dc.identifier.citationXu, Y., Lam, K.F., Cheung, Y.B. (2014-06-15). Estimation of intervention effects using recurrent event time data in the presence of event dependence and a cured fraction. Statistics in Medicine 33 (13) : 2263-2274. ScholarBank@NUS Repository. https://doi.org/10.1002/sim.6093
dc.identifier.issn10970258
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/110065
dc.description.abstractRecurrent event data with a fraction of subjects having zero event are often seen in randomized clinical trials. Those with zero event may belong to a cured (or non-susceptible) fraction. Event dependence refers to the situation that a person's past event history affects his future event occurrences. In the presence of event dependence, an intervention may have an impact on the event rate in the non-cured through two pathways-a primary effect directly on the outcome event and a secondary effect mediated through event dependence. The primary effect combined with the secondary effect is the total effect. We propose a frailty mixture model and a two-step estimation procedure for the estimation of the effect of an intervention on the probability of cure and the total effect on event rate in the non-cured. A summary measure of intervention effects is derived. The performance of the proposed model is evaluated by simulation. Data on respiratory exacerbations from a randomized, placebo-controlled trial are re-analyzed for illustration. © 2014 John Wiley & Sons, Ltd.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1002/sim.6093
dc.sourceScopus
dc.subjectEvent dependence
dc.subjectFrailty mixture model
dc.subjectIntervention effects
dc.subjectRecurrent events
dc.typeArticle
dc.contributor.departmentDUKE-NUS GRADUATE MEDICAL SCHOOL S'PORE
dc.description.doi10.1002/sim.6093
dc.description.sourcetitleStatistics in Medicine
dc.description.volume33
dc.description.issue13
dc.description.page2263-2274
dc.description.codenSMEDD
dc.identifier.isiut000335772800008
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