Using Multiple Comparison Groups to Address Unobserved Biases in Comparative Effectiveness Research

Frank B. Yoon, Haiden A. Huskamp, Alisa B. Busch and Sharon-Lise T. Normand

Mathematica Policy Research Reports from Mathematica Policy Research

Abstract: Studies of large policy interventions typically do not involve randomization. Adjustments, such as matching, can remove the bias due to observed covariates, but residual confounding remains a concern.

Keywords: Causal inference; Fine balance; Quasi-experiments; Testing in order (search for similar items in EconPapers)
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