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- Publisher Website: 10.1111/j.0006-341X.2005.030815.x
- Scopus: eid_2-s2.0-15044342852
- PMID: 15737088
- WOS: WOS:000227576600017
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Article: Quantile regression models with multivariate failure time data
Title | Quantile regression models with multivariate failure time data |
---|---|
Authors | |
Keywords | Bootstrap Correlation Estimating equations Kaplan-Meier estimator Perturbation Regression quantile |
Issue Date | 2005 |
Publisher | Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/BIOM |
Citation | Biometrics, 2005, v. 61 n. 1, p. 151-161 How to Cite? |
Abstract | As an alternative to the mean regression model, the quantile regression model has been studied extensively with independent failure time data. However, due to natural or artificial clustering, it is common to encounter multivariate failure time data in biomedical research where the intracluster correlation needs to be accounted for appropriately. For right-censored correlated survival data, we investigate the quantile regression model and adapt an estimating equation approach for parameter estimation under the working independence assumption, as well as a weighted version for enhancing the efficiency. We show that the parameter estimates are consistent and asymptotically follow normal distributions. The variance estimation using asymptotic approximation involves nonparametric functional density estimation. We employ the bootstrap and perturbation resampling methods for the estimation of the variance-covariance matrix. We examine the proposed method for finite sample sizes through simulation studies, and illustrate it with data from a clinical trial on otitis media. |
Persistent Identifier | http://hdl.handle.net/10722/146558 |
ISSN | 2022 Impact Factor: 1.9 2020 SCImago Journal Rankings: 2.298 |
ISI Accession Number ID | |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yin, G | en_HK |
dc.contributor.author | Cai, J | en_HK |
dc.date.accessioned | 2012-05-02T08:37:00Z | - |
dc.date.available | 2012-05-02T08:37:00Z | - |
dc.date.issued | 2005 | en_HK |
dc.identifier.citation | Biometrics, 2005, v. 61 n. 1, p. 151-161 | en_HK |
dc.identifier.issn | 0006-341X | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/146558 | - |
dc.description.abstract | As an alternative to the mean regression model, the quantile regression model has been studied extensively with independent failure time data. However, due to natural or artificial clustering, it is common to encounter multivariate failure time data in biomedical research where the intracluster correlation needs to be accounted for appropriately. For right-censored correlated survival data, we investigate the quantile regression model and adapt an estimating equation approach for parameter estimation under the working independence assumption, as well as a weighted version for enhancing the efficiency. We show that the parameter estimates are consistent and asymptotically follow normal distributions. The variance estimation using asymptotic approximation involves nonparametric functional density estimation. We employ the bootstrap and perturbation resampling methods for the estimation of the variance-covariance matrix. We examine the proposed method for finite sample sizes through simulation studies, and illustrate it with data from a clinical trial on otitis media. | en_HK |
dc.language | eng | en_US |
dc.publisher | Blackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/BIOM | en_HK |
dc.relation.ispartof | Biometrics | en_HK |
dc.subject | Bootstrap | en_HK |
dc.subject | Correlation | en_HK |
dc.subject | Estimating equations | en_HK |
dc.subject | Kaplan-Meier estimator | en_HK |
dc.subject | Perturbation | en_HK |
dc.subject | Regression quantile | en_HK |
dc.subject.mesh | Biometry | en_US |
dc.subject.mesh | Child | en_US |
dc.subject.mesh | Child, Preschool | en_US |
dc.subject.mesh | Clinical Trials As Topic - Methods | en_US |
dc.subject.mesh | Cluster Analysis | en_US |
dc.subject.mesh | Graft Survival | en_US |
dc.subject.mesh | Humans | en_US |
dc.subject.mesh | Infant | en_US |
dc.subject.mesh | Multivariate Analysis | en_US |
dc.subject.mesh | Myringoplasty | en_US |
dc.subject.mesh | Otitis Media - Surgery | en_US |
dc.subject.mesh | Probability | en_US |
dc.subject.mesh | Regression Analysis | en_US |
dc.subject.mesh | Sample Size | en_US |
dc.subject.mesh | Time Factors | en_US |
dc.subject.mesh | Treatment Failure | en_US |
dc.title | Quantile regression 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 | 10.1111/j.0006-341X.2005.030815.x | en_HK |
dc.identifier.pmid | 15737088 | - |
dc.identifier.scopus | eid_2-s2.0-15044342852 | en_HK |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-15044342852&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 61 | en_HK |
dc.identifier.issue | 1 | en_HK |
dc.identifier.spage | 151 | en_HK |
dc.identifier.epage | 161 | en_HK |
dc.identifier.isi | WOS:000227576600017 | - |
dc.publisher.place | United Kingdom | en_HK |
dc.identifier.scopusauthorid | Yin, G=8725807500 | en_HK |
dc.identifier.scopusauthorid | Cai, J=7403153136 | en_HK |
dc.identifier.citeulike | 110092 | - |
dc.identifier.issnl | 0006-341X | - |