Validation studies using an alloyed gold standard.

Abstract

A key assumption made when using a validation study to correct an estimate of relative risk for bias due to misclassification or measurement error is that the available measure, known to have error but nonetheless used routinely in the main study, is compared to a gold standard measured without error. In most epidemiologic applications, the putative gold standard is in fact measured with error. The effect of the violation of the assumption on the corrected estimate depends on the magnitudes of the errors in the two measures and on their correlation. In particular, when the errors are negatively correlated, independent, or weakly positively correlated, the corrected estimate will tend to overcorrect beyond the true value.