Exposure Measurement Error Bias Amplification
Abstract Consider an observational study of the association between a continuous exposure and outcome, where the exposure variable of primary interest suffers classical measurement error (i.e., the measured exposures are distributed around the true exposure with independent error). In the absence of exposure measurement error, it is widely recognized that one should control for confounders of the association of interest to obtain an unbiased estimate of the effect of that exposure on the outcome of interest. However, we show that, in the presence of classical exposure measurement error, the net bias in an estimate of the association of interest may increase upon adjustment for confounders. We offer an analytical expression for the change in net bias in an estimate of the association of interest upon adjustment for a confounder in the presence of classical exposure measurement error, and illustrate this problem using simulations.