What are the Assumptions of Regression Calibration?
Regression calibration relies on several assumptions:
The measurement error is non-differential, meaning it is independent of the outcome. The validation study is representative of the main study population. The calibration model is correctly specified, i.e., it accurately describes the relationship between observed and true exposures.
Violations of these assumptions can affect the validity and efficiency of the regression calibration estimates.
