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A modified partial likelihood score method for Cox regression with covariate error under the internal validation design.

David M ZuckerXin ZhouXiaomei LiaoYi LiDonna Spiegelman
Published in: Biometrics (2019)
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 the Health Professionals Follow-Up Study (HPFS) on the effect of diet on incidence of Type II diabetes.
Keyphrases
  • electronic health record
  • type diabetes
  • cardiovascular disease
  • healthcare
  • big data
  • risk factors
  • weight loss
  • machine learning
  • adipose tissue