Semiparametric regression of clustered current status data

ABSTRACT

This paper discusses regression analysis of clustered current status data under semiparametric additive hazards models. In particular, we consider the situation when cluster sizes can be informative about correlated failure times from the same cluster. To address the problem, we present estimating equation-based estimation procedures and establish asymptotic properties of the resulting estimates. Finite sample performance of the proposed method is assessed through an extensive simulation study, which indicates the procedure works well. The method is applied to a motivating data set from a lung tumorigenicity study.

KEYWORDS:

• Additive hazards model
• correlated failure times
• current status data
• partial likelihood
• weighted estimating equation

2010 MATHEMATICS SUBJECT CLASSIFICATION:

• 62N02

Acknowledgements

The authors wish to thank the editor, the associate editor and the referees for their valuable comments and suggestions, which greatly improved the article.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was partially supported by the National Natural Science Foundation of China [grant number 11471252] to the first and second authors.