Measurement error in proportional hazards models for survival data with long-term survivors |
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Authors: | Xiao-bing Zhao Xian Zhou |
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Institution: | 1. School of Mathematics and Statistics, Zhejiang University of Finance and Economics, Hangzhou, 310018, China 2. Department of Applied Finance and Actuarial Studies, Macquarie University, North Ryde, Sydney, NSW, 2109, Australia
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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. |
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Keywords: | proportional hazards counting process long-term survivor measurement error corrected score function |
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