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Baseline, Placebo, and Treatment: Efficient Estimation for Three-Group Experiments

  • Alan S. Gerber (a1), Donald P. Green (a1), Edward H. Kaplan (a2) and Holger L. Kern (a3)


Randomized experiments commonly compare subjects receiving a treatment to subjects receiving a placebo. An alternative design, frequently used in field experimentation, compares subjects assigned to an untreated baseline group to subjects assigned to a treatment group, adjusting statistically for the fact that some members of the treatment group may fail to receive the treatment. This article shows the potential advantages of a three-group design (baseline, placebo, and treatment). We present a maximum likelihood estimator of the treatment effect for this three-group design and illustrate its use with a field experiment that gauges the effect of prerecorded phone calls on voter turnout. The three-group design offers efficiency advantages over two-group designs while at the same time guarding against unanticipated placebo effects (which would undermine the placebo-treatment comparison) and unexpectedly low rates of compliance with the treatment assignment (which would undermine the baseline-treatment comparison).


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Authors' note: The authors are grateful to Mark Grebner, who conceived of the intervention described here and assisted in data collection, and to the Institution for Social and Policy Studies. We also thank the editors and anonymous reviewers, who provided very valuable comments. The experiment reported in this article was reviewed and approved by the Human Subjects Committee at Yale University. Supplementary materials for this article are available on the Political Analysis Web site.



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Baseline, Placebo, and Treatment: Efficient Estimation for Three-Group Experiments

  • Alan S. Gerber (a1), Donald P. Green (a1), Edward H. Kaplan (a2) and Holger L. Kern (a3)


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