Methodology to correct for differential misclassification.

Misclassification of exposure is a serious problem in epidemiology. Methods for addressing misclassification are available, but most are based on limiting assumptions such as availability of a "gold standard" measure of true exposure, or availability of two tests of exposure whose performance is nondifferential. In this paper, we discuss a method that allows the investigator to correct for differential misclassification in case-control studies. Our method only requires two potentially imperfect tests for measuring exposure. Importantly, the sensitivity and specificity of each test when applied to cases may differ from the sensitivity and specificity when applied to controls. The approach does require two subgroups of cases, such that each test's sensitivity and specificity is the same across these subgroups and requires analogous subgroups for controls. We exemplify our approach in several ways, using hypothetical data, using data from a case-control study of birth defects and service in Vietnam, and by a small Monte Carlo study. Finally, we discuss limitations of the method.

Duke Scholars

Author Andrzej Stanislaw Kosinski Biostatistics & Bioinformatics, Division of Biostatistics