title: ANALYSIS OF MULTIVARIATE FAILURE TIME DATA USING MARGINAL PROPORTIONAL HAZARDS MODEL.
abstract: The marginal proportional hazards model is an important tool in the analysis of multivariate failure time data in the presence of censoring. We propose a method of estimation via the linear combinations of martingale residuals. The estimation and inference procedures are easy to implement numerically. The estimation is generally more accurate than the existing pseudo-likelihood approach: the size of efficiency gain can be considerable in some cases, and the maximum relative efficiency in theory is infinite. Consistency and asymptotic normality are established. Empirical evidence in support of the theoretical claims is shown in simulation studies.
authors.affiliation: School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai 200433, China. ychen@mail.shufe.edu.cn.
authors.forename: Ying
authors.initials: Y
authors.lastname: Chen
authors.forename: Kani
authors.initials: K
authors.lastname: Chen
authors.forename: Zhiliang
authors.initials: Z
authors.lastname: Ying
keywords: Alternating projection; counting process martingale; marginal likelihood; martingale residual; semiparametric efficiency