Blind assignment of exposure does not always prevent differential misclassification.

The authors argue that one can never be certain whether an exposure variable which is measured with error is subject to differential misclassification in either a case-control study or a cohort study. They present hypothetic examples that demonstrate that even when misclassification is nondifferential in a 2 x 3 table, the observed odds ratios in the 2 x 2 table created by collapsing over two exposure levels can be either in the opposite direction from or more extreme than the odds ratio that would be obtained if exposures were classified correctly. The anomalies are explained by the observation that the 2 x 2 tables exhibit differential misclassification. In general, collapsing over categories which have different risks of disease and different probabilities of exposure misclassification can induce differential misclassification and even nonconservative estimates of relative risk. Collapsing of exposure levels can occur in the analysis or at the exposure assessment stage. Since indistinguishable categories can be collapsed implicitly, blind assessment of exposure, i.e., assignment without knowledge of disease status, does not guarantee that misclassification is nondifferential.