Regression calibration is a statistical technique used to correct for measurement error in exposure variables. In epidemiological studies, exposure variables (such as diet, physical activity, or pollutant levels) are often measured with error. This error can lead to biased estimates of the association between exposure and outcome. Regression calibration aims to reduce this bias by adjusting the observed exposure values based on information from a validation study or a subset of the main study where the exposures are measured more accurately.
