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Bayesian Expectancy Invalidates Double-Blind Randomized Controlled Medical Trials

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  • Chemla, Gilles
  • Hennessy, Christopher

Abstract

Double-blind RCTs are viewed as the gold standard in eliminating placebo effects and identifying non-placebo physiological effects. Expectancy theory posits that subjects have better present health in response to better expected future health. We show that if subjects Bayesian update about efficacy based upon physiological responses during a single-stage RCT, expected placebo effects are generally unequal across treatment and control groups. Thus, the difference between mean health across treatment and control groups is a biased estimator of the mean non-placebo physiological effect. RCTs featuring low treatment probabilities are robust: Bias approaches zero as the treated group measure approaches zero.

Suggested Citation

  • Chemla, Gilles & Hennessy, Christopher, 2016. "Bayesian Expectancy Invalidates Double-Blind Randomized Controlled Medical Trials," CEPR Discussion Papers 11360, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:11360
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    References listed on IDEAS

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    1. Angus Deaton, 2010. "Instruments, Randomization, and Learning about Development," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 424-455, June.
    2. 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.
    3. repec:pri:rpdevs:deaton_instruments_randomization_learning_all_04april_2010 is not listed on IDEAS
    4. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769, April.
    5. 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.
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    More about this item

    Keywords

    Bayesian updating; bias; control; double-blind RCTs; drug; placebo; treatment;
    All these keywords.

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