Acta mathematica scientia,Series A ›› 2014, Vol. 34 ›› Issue (3): 530-539.

• Articles • Previous Articles     Next Articles

A General Class of Marginal Semiparametric Hazards Model with Multivariate Failure Time Data

 YANG Qing-Long1, GUO Li-Sha2, LIU Yan-Yan3   

  1. 1.Zhongnan University of Economics and Law, Wuhan 430073;
    2.School of Mathematics and Statistics, South Central University for Nationalities, Wuhan 430073;
    3.School of Mathematics and Statistics, Wuhan University, Wuhan 430072
  • Received:2012-02-11 Revised:2013-12-13 Online:2014-06-25 Published:2014-06-25
  • Supported by:

    国家自然科学基金 (11171263,  11301545)和中南财经政法大学基本科研业务费青年教师创新项目(20132051) 资助

Abstract:

Multivariate failure time data are frequently encountered in biomedical research. In this article,  we propose a general class of hazards regression model for multivariate failure time data. This general class includes some popular classes of models as subclasses,  such as marginal proportional hazards model, the marginal accelerated failure time model.
 Regression coefficients are estimated through estimating equation method. The proposed estimators for the  regression parameters are shown asymptotically to follow a multivariate normal distribution with a sandwich-type
covariance matrix that can be consistently estimated. The estimated subject-specific cumulative baseline hazard process is  shown to converge weakly to a zero mean Gaussian random field.

Key words: Multivariate failure time, Marginal hazards model, Estimating equation, Asymptotic normality

CLC Number: 

  • 62G05
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