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A Simple, Graphical Approach to Comparing Multiple Treatments

Author

Listed:
  • Brennan S. Thompson

    (Department of Economics, Ryerson University)

  • Matthew D. Webb

    (Department of Economics, Carleton University)

Abstract

We propose a graphical approach to comparing multiple treatments that allows users to easily infer differences between any treatment effect and zero, and between any pair of treatment effects. Our approach makes use of a flexible, resampling-based procedure that asymptotically controls the familywise error rate (the probability of making one or more spurious inferences). We demonstrate the usefulness of our approach with three empirical examples.

Suggested Citation

  • Brennan S. Thompson & Matthew D. Webb, 2015. "A Simple, Graphical Approach to Comparing Multiple Treatments," Working Papers 063, Toronto Metropolitan University, Department of Economics, revised Mar 2017.
    • Handle: RePEc:rye:wpaper:wp063
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    References listed on IDEAS

    as
    1. Anderson, Michael L., 2008. "Multiple Inference and Gender Differences in the Effects of Early Intervention: A Reevaluation of the Abecedarian, Perry Preschool, and Early Training Projects," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1481-1495.
    2. John A. List & Azeem M. Shaikh & Yang Xu, 2019. "Multiple hypothesis testing in experimental economics," Experimental Economics, Springer;Economic Science Association, vol. 22(4), pages 773-793, December.
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    9. Steven F. Lehrer & R. Vincent Pohl & Kyungchul Song, 2022. "Multiple Testing and the Distributional Effects of Accountability Incentives in Education," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1552-1568, October.
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