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Abstract
The difference in difference (DID) design is a quasi-experimental research design
that researchers often use to study causal relationships in public health settings
where randomized controlled trials (RCTs) are infeasible or unethical. However, causal
inference poses many challenges in DID designs. In this article, we review key features
of DID designs with an emphasis on public health policy research. Contemporary researchers
should take an active approach to the design of DID studies, seeking to construct
comparison groups, sensitivity analyses, and robustness checks that help validate
the method's assumptions. We explain the key assumptions of the design and discuss
analytic tactics, supplementary analysis, and approaches to statistical inference
that are often important in applied research. The DID design is not a perfect substitute
for randomized experiments, but it often represents a feasible way to learn about
casual relationships. We conclude by noting that combining elements from multiple
quasi-experimental techniques may be important in the next wave of innovations to
the DID approach.