Regression analysis of clustered interval-censored failure time data with the additive hazards model

Abstract

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.

Keywords:

• additive hazards model
• clustered data
• estimating equation
• interval censoring
• semi-parametric regression analysis

Acknowledgements

The authors are grateful to the editor and the reviewers for their insightful comments on the article. This work was partially supported by NIH grant 5 R01 CA152035 to the third author.