Measurement error in epidemiology: The design of validation studies - I: Univariate situation

It is becoming standard practice in epidemiology to adjust relative risk es timates to remove the bias caused by non-differential errors in the exposur e measurement. Estimation of the correction factor is often based on a vali dation study incorporating repeated measures of exposure, which are assumed to be independent. This assumption is difficult to verify and often likely to be false. We examine the effect of departures from this assumption on t he correction factor estimate, and explore the design of validation studies using two or even three different types of measurement of exposure, where assumption of independence between the measures may be more realistic. The value of good biomarker measures of exposure is demonstrated even if they a re feasible to use only in a validation study. Copyright (C) 1999 John Wile y & Sons, Ltd.