Yang, Qinglong; Guo, Lisha; Liu, Yanyan A general class of marginal semiparametric hazards models with multivariate failure time data. (Chinese. English summary) Zbl 1313.62146 Acta Math. Sci., Ser. A, Chin. Ed. 34, No. 3, 530-539 (2014). Summary: Multivariate failure time data are frequently encountered in biomedical research. In this article, we propose a general class of hazards regression models 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 an 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. MSC: 62N05 Reliability and life testing 62N01 Censored data models 62H12 Estimation in multivariate analysis 62G05 Nonparametric estimation 62G20 Asymptotic properties of nonparametric inference Keywords:multivariate failure time; marginal hazards model; estimating equation; asymptotic normality PDFBibTeX XMLCite \textit{Q. Yang} et al., Acta Math. Sci., Ser. A, Chin. Ed. 34, No. 3, 530--539 (2014; Zbl 1313.62146)