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Biometrics. 2018 Dec 7. doi: 10.1111/biom.13012. [Epub ahead of print]

A Modified Partial Likelihood Score Method for Cox Regression with Covariate Error Under the Internal Validation Design.

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Department of Statistics and Data Science, The Hebrew University of Jerusalem, Mount Scopus, Jerusalem 91905, Israel.
Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA.
Department of Biostatistics, University of Michigan School of Public Health, 1415 Washington Heights, Ann Arbor, MI 48109-2029, USA.
Department of Biostatistics, Yale School of Public Health and Department of Statistics, Yale University, New Haven, CT 06520, USA.
Departments of Epidemiology, Biostatistics, Nutrition and Global Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.


We develop a new method for covariate error correction in the Cox survival regression model, given a modest sample of internal validation data. Unlike most previous methods for this setting, our method can handle covariate error of arbitrary form. Asymptotic properties of the estimator are derived. In a simulation study, the method was found to perform very well in terms of bias reduction and confidence interval coverage. The method is applied to data from Health Professionals Follow-Up Study (HPFS) on the effect of diet on incidence of Type II diabetes. This article is protected by copyright. All rights reserved.


Cox model; Measurement error; modified score


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