Additive Mixed Effect Model for Clustered Doubly Censored Data

Abstract

Cai and Zeng (2011) proposed an additive mixed effect model to analyze clustered right-censored data. In this article, we demonstrate that the approach of Cai and Zeng (2011) can be extended to clustered doubly censored data. Furthermore, when both left- and right-censoring variables are always observed, we propose alternative estimators using the approach of Cai and Cheng (2004). A simulation study is conducted to investigate the performance of the proposed estimators.

Keywords:

• Additive model
• Estimating equation
• Left-censoring

Mathematics Subject Classification:

• Primary 62N01
• Secondary 62N02

Acknowledgments

The author would like to thank the associate editor and referees for their helpful and valuable comments and suggestions.