Journal
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE
Volume 43, Issue 3, Pages 454-480Publisher
WILEY
DOI: 10.1002/cjs.11258
Keywords
additive error model; Berkson error model; corrected score; covariate measurement error; Cox model; model misspecification; profile likelihood
Categories
Funding
- Natural Sciences and Engineering Research Council of Canada
- Trainee Award of The CANNeCTIN Biostatistics and Methodological Innovation Program
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In survival analysis, covariate measurement error has been studied extensively for the Cox model. In this article, we propose a corrected profile likelihood approach, and show that many existing methods can be unified by our approach. Furthermore, we extend our discussion to general measurement error and Berkson models, as opposed to the classical additive error model that has been widely used in the literature. We investigate the impact of model misspecification of the measurement error process and uncover interesting findings. Empirical studies are carried out to illustrate the usage of the proposed methods and to assess their performance. (c) 2015 Statistical Society of Canada
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