A semiparametric random effects model for multivariate competing risks data

• 成果类型: Article
• 署名作者: Scheike, Thomas H.; Sun, Yanqing; Zhang, Mei-Jie; Jensen, Tina Kold
• 署名单位: University of Copenhagen; University of North Carolina; University of North Carolina Charlotte; Medical College of Wisconsin; University of Southern Denmark
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asp082
• 发表日期: 2010
• 页码: 133145
• 关键词: PROPORTIONAL HAZARDS MODEL; failure time associations; nonparametric-estimation; cumulative incidence; REGRESSION-MODEL; subdistribution; distributions; ratio

摘要

We propose a semiparametric random effects model for multivariate competing risks data when the failures of a particular type are of interest. Under this model, the marginal cumulative incidence functions follow a generalized semiparametric additive model. The associations between the cause-specific failure times can be studied through dependence parameters of copula functions that are allowed to depend on cluster-level covariates. A cross-odds ratio-type measure is proposed to describe the associations between cause-specific failure times, and its relationship to the dependence parameters is explored. We develop a two-stage estimation procedure where the marginal models are estimated in the first stage and the dependence parameters are estimated in the second stage. The large sample properties of the proposed estimators are derived. The proposed procedures are applied to Danish twin data to model the cumulative incidence for the age of natural menopause and to investigate the association in the onset of natural menopause between monozygotic and dizygotic twins.