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Epidemiologists frequently study the experience of a population over time to estimate the association between exposure and outcome. These studies generally use case–control, prospective cohort, or retrospective cohort designs. The “cross-sectional cohort study,” as it is termed here, represents an alternative to these standard methods. With this design, an investigator samples a source population cross-sectionally and then retrospectively assesses subjects’ histories of exposures and outcomes over a specified time period. Certain threats to validity, such as nonignorable exiting and measurement error from retrospective assessments, must be considered carefully when using this design. However, in some situations, the cross-sectional cohort design may offer advantages over traditional designs—especially in studies in which there is a long interval between exposures and outcomes, in which exposures and outcomes can be accurately assessed retrospectively, and in which the outcome does not accelerate any exiting from the population. Such situations often arise when studying chronic or episodic conditions with low mortality, such as psychiatric disorders.