The Impact of Joint Misclassification of Exposures and Outcomes on the Results of Epidemiologic Research

AbstractPurpose of ReviewWe discuss the causes and impacts of dependent nondifferential misclassification with particular attention to the mechanisms by which dependent misclassification occurs. We also present suggestions for how to reduce the potential for dependent misclassification.Recent FindingsMisclassification is ubiquitous in associations between exposures and outcomes in epidemiology. While most epidemiologic textbooks cover independent nondifferential misclassification of both exposures and outcomes, the impact of joint misclassification of exposure and outcome is a poorly understood problem.SummaryUnder common scenarios, joint misclassification of exposure and outcome can lead to strong bias (in any direction) even when the misclassification of both variables is nondifferential. The direction and magnitude of the bias will depend on the amount of dependent error and the mechanism by which the dependencies occur, as well as the direction and magnitude of the true effect along with the extent to which additional independent nondifferential misclassification of exposures or outcomes also exists.

Source: Current Epidemiology Reports - April 20, 2018 Category: Epidemiology Source Type: research