Background. It is generally agreed that adjustment for measurement error (when feasible)
can substantially increase the validity of epidemiologic analyses. Although a broad variety of
methods for measurement error correction has been developed, application in practice is
rare. One reason may be that little is known about the robustness of these methods against
violations of their restrictive assumptions. Methods. We carried out a simulation study to
assess the performance of two error correction methods (a regression calibration method …