On the impact of misclassification in an ordinal exposure variable

Abstract

Say that interest focuses on the relationship between an exposure variable and an outcome variable; however, the exposure variable is subject to measurement error. While exceptions have been identified, in almost all circumstances nondifferential measurement error leads to attenuated regression coefficients and lost power to detect associations. In the case of an ordinal exposure variable subject to nondifferential misclassification, we confirm that power is always lost in a general test for association between the exposure and outcome variables. Surprisingly, however, we find that for a linear test of trend, a gain in power is possible.