A Class of Functional Methods for Error-Contaminated Survival Data Under Additive Hazards Models with Replicate Measurements
重复测量下含测量误差生存数据的加性风险函数校正方法
Covariate measurement error has attracted extensive interest in survival analysis. Since Prentice, a large number of inference methods have been developed to handle error-prone data that are modulated with proportional hazards models. In contrast to proportional hazards models, additive hazards models offer a flexible tool to delineate survival processes. However, there is little research on measurement error effects under additive hazards models. In this article, we…