Causal Covariate Selection for the Imputation-based Regression Calibration Method for Exposure Measurement Error Bias Correction
暴露测量误差插补型回归校准的因果协变量选择
In this paper, we identify the criteria for the selection of the minimal and most efficient covariate adjustment sets for the regression calibration method developed by Carroll, Rupert and Stefanski (CRS, 1992), used to correct bias due to continuous exposure measurement error. We utilize directed acyclic graphs to illustrate how subject matter knowledge can aid in the selection of such adjustment sets. Valid measurement error correction requires the collection of data on…