ABSTRACT
Regression calibration (Chapter 4) and SIMEX (Chapter 5) are widely applicable, general methods for eliminating or reducing measurement error bias. These methods result in estimators that are consistent in important special cases, such as linear regression and loglinear mean models, but that are only approximately consistent in general.
