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Identifying Placebo Effects with Data from Clinical Trials

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  • Anup Malani

Abstract

A medical treatment is said to have placebo effects if patients who are optimistic about the treatment respond better to the treatment. This paper proposes a simple test for placebo effects. Instead of comparing the treatment and control arms of a single trial, one should compare the treatment arms of two trials with different probabilities of assignment to treatment. If there are placebo effects, patients in the higher-probability trial will experience better outcomes simply because they believe that there is a greater chance of receiving treatment. This paper finds evidence of placebo effects in trials of antiulcer and cholesterol-lowering drugs.

Suggested Citation

  • Anup Malani, 2006. "Identifying Placebo Effects with Data from Clinical Trials," Journal of Political Economy, University of Chicago Press, vol. 114(2), pages 236-256, April.
    • Handle: RePEc:ucp:jpolec:v:114:y:2006:i:2:p:236-256
    DOI: 10.1086/500279
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    Cited by:

    1. Roberto Ippoliti, 2013. "The market of human experimentation," European Journal of Law and Economics, Springer, vol. 35(1), pages 61-85, February.
    2. Chad D. Meyerhoefer & Muzhe Yang, 2011. "The Relationship between Food Assistance and Health: A Review of the Literature and Empirical Strategies for Identifying Program Effects," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 33(3), pages 304-344.
    3. Sylvain Chassang & Erik Snowberg & Ben Seymour & Cayley Bowles, 2015. "Accounting for Behavior in Treatment Effects: New Applications for Blind Trials," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-13, June.
    4. van den Berg, Gerard J., 2007. "An Economic Analysis of Exclusion Restrictions for Instrumental Variable Estimation," IZA Discussion Papers 2585, Institute of Labor Economics (IZA).
    5. Jens Ludwig & Jeffrey R. Kling & Sendhil Mullainathan, 2011. "Mechanism Experiments and Policy Evaluations," Journal of Economic Perspectives, American Economic Association, vol. 25(3), pages 17-38, Summer.
    6. Sylvain Chassang & Gerard Padro I Miquel & Erik Snowberg, 2012. "Selective Trials: A Principal-Agent Approach to Randomized Controlled Experiments," American Economic Review, American Economic Association, vol. 102(4), pages 1279-1309, June.
    7. Chemla, Gilles & Hennessy, Christopher, 2016. "Subject Rational Expectations Will Contaminate Randomized Controlled Medical Trials," CEPR Discussion Papers 11360, C.E.P.R. Discussion Papers.
    8. Jose M. Fernandez, 2013. "An Empirical Model Of Learning Under Ambiguity: The Case Of Clinical Trials," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(2), pages 549-573, May.
    9. Gani Aldashev & Georg Kirchsteiger & Alexander Sebald, 2017. "Assignment Procedure Biases in Randomised Policy Experiments," Economic Journal, Royal Economic Society, vol. 127(602), pages 873-895, June.
    10. Adam Leive & Thomas Stratmann, 2015. "Do national cancer screening guidelines reduce mortality?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 28(4), pages 1075-1095, October.
    11. Anup Malani & Tomas J. Philipson, 2011. "Can Medical Progress be Sustained? Implications of the Link Between Development and Output Markets," NBER Working Papers 17011, National Bureau of Economic Research, Inc.
    12. Steven D. Levitt & John A. List, 2011. "Was There Really a Hawthorne Effect at the Hawthorne Plant? An Analysis of the Original Illumination Experiments," American Economic Journal: Applied Economics, American Economic Association, vol. 3(1), pages 224-238, January.
    13. Tat Y. Chan & Barton H. Hamilton, 2006. "Learning, Private Information, and the Economic Evaluation of Randomized Experiments," Journal of Political Economy, University of Chicago Press, vol. 114(6), pages 997-1040, December.
    14. Roberto Ippoliti, 2012. "Making profits working on patients’ expectations, a behavioral analysis of pharmaceutical clinical research," Journal of Bioeconomics, Springer, vol. 14(3), pages 217-241, October.
    15. Virat Agrawal & Neeraj Sood & Christopher M. Whaley, 2022. "The Ex-Ante Moral Hazard Effects of COVID-19 Vaccines," NBER Working Papers 30602, National Bureau of Economic Research, Inc.
    16. Armando Franco & Dana P. Goldman & Adam Leive & Daniel McFadden, 2017. "A Cautionary Tale in Comparative Effectiveness Research: Pitfalls and Perils of Observational Data Analysis," NBER Chapters, in: Measuring and Modeling Health Care Costs, pages 55-80, National Bureau of Economic Research, Inc.
    17. Chemla, Gilles & Hennessy, Christopher A., 2019. "Controls, belief updating, and bias in medical RCTs," Journal of Economic Theory, Elsevier, vol. 184(C).

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