Measurement error in proportional hazards models for survival data with long-term survivors

Xiao Bing Zhao*, Xian Zhou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This work studies a proportional hazards model for survival data with "long-term survivors", in which covariates are subject to linear measurement error. It is well known that the naive estimators from both partial and full likelihood methods are inconsistent under this measurement error model. For measurement error models, methods of unbiased estimating function and corrected likelihood have been proposed in the literature. In this paper, we apply the corrected partial and full likelihood approaches to estimate the model and obtain statistical inference from survival data with long-term survivors. The asymptotic properties of the estimators are established. Simulation results illustrate that the proposed approaches provide useful tools for the models considered.

Original languageEnglish
Pages (from-to)275-288
Number of pages14
JournalActa Mathematicae Applicatae Sinica
Volume28
Issue number2
DOIs
Publication statusPublished - May 2012

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