Qixuan Chen, Hanga Galfalvy, Naihua Duan
Objectives. We explore how misclassification in disease status can distort the exposure-disease association in a study with dichotomous disease and exposure status. Methods. We define the difference in population odds ratios between populations with and without disease misclassification as population-level bias and derive the bias as a function of sensitivity and specificity for observed disease status. The magnitude and direction of bias can be elucidated through analytic derivations, as illustrated with numerical examples. Results. Patterns of bias exist not only for nondifferential misclassification but also for some differential misclassification scenarios. We have provided conditions defined in terms of sensitivity and specificity that correspond to each pattern of bias. Conclusions. Caution is needed in interpreting results when misclassification is present. Our findings can be used to assess the effects of disease misclassification in a population when sensitivity and specificity are known or can be estimated. [ABSTRACT FROM AUTHOR]
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