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- Publisher Website: 10.1002/sim.6093
- Scopus: eid_2-s2.0-84899952736
- PMID: 24449504
- WOS: WOS:000335772800008
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Article: Estimation of Intervention Effects Using Recurrent Event Time Data in the Presence of Event Dependence and a Cured Fraction
Title | Estimation of Intervention Effects Using Recurrent Event Time Data in the Presence of Event Dependence and a Cured Fraction |
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Authors | |
Keywords | Event dependence Frailty mixture model Intervention effects Recurrent events |
Issue Date | 2014 |
Publisher | John Wiley & Sons. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0277-6715/ |
Citation | Statistics in Medicine, 2014, v. 33n. 13, p. 2263-2274 How to Cite? |
Abstract | Recurrent 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. |
Persistent Identifier | http://hdl.handle.net/10722/203416 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Xu, Y | en_US |
dc.contributor.author | Lam, KF | en_US |
dc.contributor.author | Cheung, YB | en_US |
dc.date.accessioned | 2014-09-19T15:10:24Z | - |
dc.date.available | 2014-09-19T15:10:24Z | - |
dc.date.issued | 2014 | en_US |
dc.identifier.citation | Statistics in Medicine, 2014, v. 33n. 13, p. 2263-2274 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/203416 | - |
dc.description.abstract | Recurrent 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. | en_US |
dc.language | eng | en_US |
dc.publisher | John Wiley & Sons. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0277-6715/ | en_US |
dc.relation.ispartof | Statistics in Medicine | en_US |
dc.rights | Statistics in Medicine. Copyright © John Wiley & Sons. | en_US |
dc.subject | Event dependence | - |
dc.subject | Frailty mixture model | - |
dc.subject | Intervention effects | - |
dc.subject | Recurrent events | - |
dc.title | Estimation of Intervention Effects Using Recurrent Event Time Data in the Presence of Event Dependence and a Cured Fraction | en_US |
dc.type | Article | en_US |
dc.identifier.email | Lam, KF: hrntlkf@hkucc.hku.hk | en_US |
dc.identifier.authority | Lam, KF=rp00718 | en_US |
dc.identifier.doi | 10.1002/sim.6093 | en_US |
dc.identifier.pmid | 24449504 | - |
dc.identifier.scopus | eid_2-s2.0-84899952736 | - |
dc.identifier.hkuros | 235534 | en_US |
dc.identifier.volume | 33 | en_US |
dc.identifier.spage | 2263 | en_US |
dc.identifier.epage | 2274 | en_US |
dc.identifier.isi | WOS:000335772800008 | - |