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- Publisher Website: 10.1002/sim.3371
- Scopus: eid_2-s2.0-60849099675
- PMID: 18618427
- WOS: WOS:000261143200009
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Article: Bayesian transformation cure frailty models with multivariate failure time data.
Title | Bayesian transformation cure frailty models with multivariate failure time data. |
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Authors | |
Keywords | Bayesian inference Box-Cox transformation Correlated survival data Cure rate model Model selection |
Issue Date | 2008 |
Publisher | John Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0277-6715/ |
Citation | Statistics In Medicine, 2008, v. 27 n. 28, p. 5929-5940 How to Cite? |
Abstract | We propose a class of transformation cure frailty models to accommodate a survival fraction in multivariate failure time data. Established through a general power transformation, this family of cure frailty models includes the proportional hazards and the proportional odds modeling structures as two special cases. Within the Bayesian paradigm, we obtain the joint posterior distribution and the corresponding full conditional distributions of the model parameters for the implementation of Gibbs sampling. Model selection is based on the conditional predictive ordinate statistic and deviance information criterion. As an illustration, we apply the proposed method to a real data set from dentistry. |
Persistent Identifier | http://hdl.handle.net/10722/146592 |
ISSN | 2023 Impact Factor: 1.8 2023 SCImago Journal Rankings: 1.348 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Yin, G | en_HK |
dc.date.accessioned | 2012-05-02T08:37:15Z | - |
dc.date.available | 2012-05-02T08:37:15Z | - |
dc.date.issued | 2008 | en_HK |
dc.identifier.citation | Statistics In Medicine, 2008, v. 27 n. 28, p. 5929-5940 | en_HK |
dc.identifier.issn | 0277-6715 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/146592 | - |
dc.description.abstract | We propose a class of transformation cure frailty models to accommodate a survival fraction in multivariate failure time data. Established through a general power transformation, this family of cure frailty models includes the proportional hazards and the proportional odds modeling structures as two special cases. Within the Bayesian paradigm, we obtain the joint posterior distribution and the corresponding full conditional distributions of the model parameters for the implementation of Gibbs sampling. Model selection is based on the conditional predictive ordinate statistic and deviance information criterion. As an illustration, we apply the proposed method to a real data set from dentistry. | en_HK |
dc.language | eng | en_US |
dc.publisher | John Wiley & Sons Ltd. The Journal's web site is located at http://www.interscience.wiley.com/jpages/0277-6715/ | en_HK |
dc.relation.ispartof | Statistics in medicine | en_HK |
dc.subject | Bayesian inference | - |
dc.subject | Box-Cox transformation | - |
dc.subject | Correlated survival data | - |
dc.subject | Cure rate model | - |
dc.subject | Model selection | - |
dc.subject.mesh | Bayes Theorem | en_US |
dc.subject.mesh | Biometry - Methods | en_US |
dc.subject.mesh | Dentistry - Statistics & Numerical Data | en_US |
dc.subject.mesh | Disease-Free Survival | en_US |
dc.subject.mesh | Humans | en_US |
dc.subject.mesh | Likelihood Functions | en_US |
dc.subject.mesh | Models, Statistical | en_US |
dc.subject.mesh | Multivariate Analysis | en_US |
dc.subject.mesh | Proportional Hazards Models | en_US |
dc.subject.mesh | Root Canal Therapy - Methods | en_US |
dc.subject.mesh | Treatment Outcome | en_US |
dc.title | Bayesian transformation cure frailty models with multivariate failure time data. | en_HK |
dc.type | Article | en_HK |
dc.identifier.email | Yin, G: gyin@hku.hk | en_HK |
dc.identifier.authority | Yin, G=rp00831 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1002/sim.3371 | - |
dc.identifier.pmid | 18618427 | - |
dc.identifier.scopus | eid_2-s2.0-60849099675 | en_HK |
dc.identifier.volume | 27 | en_HK |
dc.identifier.issue | 28 | en_HK |
dc.identifier.spage | 5929 | en_HK |
dc.identifier.epage | 5940 | en_HK |
dc.identifier.isi | WOS:000261143200009 | - |
dc.publisher.place | United Kingdom | en_HK |
dc.identifier.scopusauthorid | Yin, G=8725807500 | en_HK |
dc.identifier.issnl | 0277-6715 | - |