Avoiding Randomization Failure in Program Evaluation, with Application to the Medicare Health Support Program
Pope, James E.
Wells, AaronNote: Order does not necessarily reflect citation order of authors.
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CitationKing, Gary, Richard Neilsen, Carter Coberley, James E. Pope, and Aaron Wells. 2011. Avoiding randomization failure in program evaluation, with application to the medicare health support program. Population Health Management 14(Suppl 1): S11-S22.
AbstractWe highlight common problems in the application of random treatment assignment in large-scale program evaluation. Random assignment is the deﬁning feature of modern experimental design, yet errors in design, implementation, and analysis often result in real-world applications not beneﬁting from its advantages. The errors discussed here cover the control of variability, levels of randomization, size of treatment arms, and power to detect causal effects, as well as the many problems that commonly lead to post-treatment bias. We illustrate these issues by identifying numerous serious errors in the Medicare Health Support evaluation and offering
recommendations to improve the design and analysis of this and other large-scale randomized experiments.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:5125263
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