An observational study is an empiric investigation of the effects of a treatment, policy, intervention, or exposure that was not randomly assigned to subjects as it would be in a randomized experiment. Observational studies are common in most fields that study people because harmful or unwanted treatments cannot be imposed on human subjects for experimental purposes. The central difficulty in an observational study is that, because treatments were not randomly assigned, the subjects receiving different treatments may not be comparable, so differing outcomes after treatment may not be effects caused by the treatment. If the treatment groups differ before treatment in ways that have been measured, there is an overt bias that often can be removed by adjustments, such as matching. There often is concern that treatment groups differed before treatment in ways that were not measured, that is, concern about hidden biases. This research project will focus on hidden biases that generally cannot be removed by adjustments and must be addressed by other means. Prior work has shown that the design of an observational study strongly affects its sensitivity to hidden biases. This project is comprised of four components. The first concerns the possibility that effect modification (a treatment by covariate interaction) may under suitable circumstances be exploited to reduce sensitivity to unmeasured biases. The second component concerns the relationship between case definition in case-control studies and sensitivity to unmeasured biases. The third concerns clustered treatment assignment and sensitivity to unmeasured biases. The final component concerns use of risk set matching to provide finer control of time dependent instrumental variables.
Observational studies are common in economics, education, epidemiology, medicine, public policy, and sociology. Improved methodology for observational studies has the potential to lead to improved policies and practices of both public and private institutions.
