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Article: Varying-association copula models for multivariate survival data

TitleVarying-association copula models for multivariate survival data
Authors
KeywordsB‐spline
confidence band
copula model
survival analysis
two‐stage estimation
Issue Date2018
PublisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1708-945X
Citation
Canadian Journal of Statistics, 2018, v. 46 n. 4, p. 556-576 How to Cite?
AbstractTo accommodate possible changes in the correlation structure of multivariate survival data, a class of varying‐association copula models is developed. The proposed model enables the association parameter to vary nonlinearly over an exposure variable, which greatly enhances the flexibility of copula models. A two‐stage estimation procedure is developed to obtain the estimators for the regression and correlation parameters. The first stage estimates the regression parameters based on the marginal proportional hazards model for each event type, and the second stage applies the B‐spline technique to estimate the varying‐association parameter by maximizing the plugged‐in likelihood function. The consistency and asymptotic normality of the proposed estimators are established, and simulation studies are conducted to examine the finite‐sample performance of our method. A real data example from the Framingham Heart Study is used to illustrate this approach. The Canadian Journal of Statistics 46: 556–576; 2018 © 2018 Société statistique du Canada
Persistent Identifierhttp://hdl.handle.net/10722/279515
ISSN
2019 Impact Factor: 0.656
2015 SCImago Journal Rankings: 0.737

 

DC FieldValueLanguage
dc.contributor.authorLi, H-
dc.contributor.authorCao, Z-
dc.contributor.authorYin, G-
dc.date.accessioned2019-11-01T07:18:51Z-
dc.date.available2019-11-01T07:18:51Z-
dc.date.issued2018-
dc.identifier.citationCanadian Journal of Statistics, 2018, v. 46 n. 4, p. 556-576-
dc.identifier.issn0319-5724-
dc.identifier.urihttp://hdl.handle.net/10722/279515-
dc.description.abstractTo accommodate possible changes in the correlation structure of multivariate survival data, a class of varying‐association copula models is developed. The proposed model enables the association parameter to vary nonlinearly over an exposure variable, which greatly enhances the flexibility of copula models. A two‐stage estimation procedure is developed to obtain the estimators for the regression and correlation parameters. The first stage estimates the regression parameters based on the marginal proportional hazards model for each event type, and the second stage applies the B‐spline technique to estimate the varying‐association parameter by maximizing the plugged‐in likelihood function. The consistency and asymptotic normality of the proposed estimators are established, and simulation studies are conducted to examine the finite‐sample performance of our method. A real data example from the Framingham Heart Study is used to illustrate this approach. The Canadian Journal of Statistics 46: 556–576; 2018 © 2018 Société statistique du Canada-
dc.languageeng-
dc.publisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1708-945X-
dc.relation.ispartofCanadian Journal of 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 using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. Postprint This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.-
dc.subjectB‐spline-
dc.subjectconfidence band-
dc.subjectcopula model-
dc.subjectsurvival analysis-
dc.subjecttwo‐stage estimation-
dc.titleVarying-association copula models for multivariate survival data-
dc.typeArticle-
dc.identifier.emailYin, G: gyin@hku.hk-
dc.identifier.authorityYin, G=rp00831-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/cjs.11474-
dc.identifier.scopuseid_2-s2.0-85056634485-
dc.identifier.hkuros308634-
dc.identifier.volume46-
dc.identifier.issue4-
dc.identifier.spage556-
dc.identifier.epage576-
dc.publisher.placeUnited States-

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