Corrected Score Function for Errors-in-Variables Models: Methodology and Application to Generalized Linear Models
本文提出一种校正得分函数的方法，用于修正自变量测量误差对参数估计的影响，并在广义线性模型中推导出具体的校正得分函数，无需额外假设即可进行推断和估计。
Statistical models whose independent variables are subject to measurement errors are often referred to as ‘errors-in-variables models’. To correct for the effects of measurement error on parameter estimation, this paper considers a correction for score functions. A corrected score function is one whose expectation with respect to the measurement error distribution coincides with the usual score function based on the unknown true independent variables. This approach makes it possible to do inference as well as estimation of model parameters without additional assumptions. The corrected score functions of some generalized linear models are obtained.