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Matching in DifferenceinDifferences: between a Rock and a Hard Place

There is intense interest in methods to measure the impacts of nonrandomized policy interventions. Differenceindifferences analysis is one such method that is increasingly popular in health policy evaluations. In 2015, Ryan, Burgess, and Dimick published a manuscript in HSR on the assumptions and optimal specifications for differenceindifferences (Ryan, Burgess, and Dimick 2015). We have referred to this paper and are grateful for Andrew Ryan's commentary on our manuscript, published in this issue of HSR, which explores how differenceindifferences using matched samples may be vulnerable to bias due to regression to the mean (RTM).

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