Local composite partial likelihood estimation for length-biased and right-censored data

ABSTRACT

Length-biased data, which are often encountered in engineering, economics and epidemiology studies, are generally subject to right censoring caused by the research ending or the follow-up loss. The structure of length-biased data is distinct from conventional survival data, since the independent censoring assumption is often violated due to the biased sampling. In this paper, a proportional hazard model with varying coefficients is considered for the length-biased and right-censored data. A local composite likelihood procedure is put forward for the estimation of unknown coefficient functions in the model, and large sample properties of the proposed estimators are also obtained. Additionally, an extensive simulation studies are conducted to assess the finite sample performance of the proposed method and a data set from the Academy Awards is analyzed.

KEYWORDS:

• Length-biased and right-censored data
• proportional hazard model
• composite partial likelihood
• varying-coefficient model

2010 MATHEMATICS SUBJECT CLASSIFICATIONS:

• 62G05
• 62N01
• 62J99

Acknowledgements

The authors wish to thank the Editor, the Associate Editor and a reviewer for their many helpful and useful comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

Zhou's work was supported by the State Key Program of National Natural Science Foundation of China (71331006), the State Key Program in the Major Research Plan of National Natural Science Foundation of China (91546202).