Regression analysis of clustered interval-censored failure time data with the additive hazards model.
This paper discusses regression analysis of clustered failure time data, which means that the failure times of interest are clustered into small groups instead of being independent. Clustering occurs in many fields such as medical studies. For the problem, a number of methods have been proposed, but most of them apply only to clustered right-censored data. In reality, the failure time data is often interval-censored. That is, the failure times of interest are known only to lie in certain intervals. We propose an estimating equation-based approach for regression analysis of clustered interval-censored failure time data generated from the additive hazards model. A major advantage of the proposed method is that it does not involve the estimation of any baseline hazard function. Both asymptotic and finite sample properties of the proposed estimates of regression parameters are established and the method is illustrated by the data arising from a lymphatic filariasis study.
Department of Statistics, University of Missouri, Columbia, MO 65211, USA.
Junlong
J
Li
Mathematics School and Institute, Jilin University, Changchun 130012, People's Republic of China.
Chunjie
C
Wang
Department of Statistics, University of Missouri, Columbia, MO 65211, USA.
Jianguo
J
Sun
additive hazards model; clustered data; estimating equation; interval censoring; semi-parametric regression analysis