Zucker David M, Zhou Xin, Liao Xiaomei, Li Yi, Spiegelman Donna
Department of Statistics, 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, Massachusetts 02115.
Biometrics. 2019 Jun;75(2):414-427. doi: 10.1111/biom.13012. Epub 2019 Apr 13.
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.
在仅有少量内部验证数据样本的情况下，我们开发了一种用于Cox生存回归模型中协变量误差校正的新方法。与此前针对该情况的大多数方法不同，我们的方法能够处理任意形式的协变量误差。我们推导了估计量的渐近性质。在一项模拟研究中，该方法在偏差减少和置信区间覆盖方面表现出色。我们将此方法应用于健康专业人员随访研究（HPFS）中关于饮食对II型糖尿病发病率影响的数据。
