Analyzing and Adjusting for Unmeasured Confounding in a Longitudinal Health Data Study
Instruction: Explain how you would identify and adjust for unmeasured confounding in a longitudinal study assessing the impact of a new health intervention.
Context: This question evaluates the candidate’s understanding of advanced techniques for dealing with unmeasured confounding in longitudinal studies. Candidates should discuss methods such as sensitivity analysis, instrumental variables, or using proxy variables. The response should include a discussion on the assumptions necessary for these methods to be valid and potential limitations in their application.
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I would first define the treatment history, outcome, time ordering, and causal effect we want. Then I would map plausible unmeasured causes of both treatment and outcome and investigate whether additional measurements are available...