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Patient enrollment in medical trials: Selection bias in a randomized experiment

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  • Malani, Anup

Abstract

Self-selection can bias estimates of treatment effects from randomized experiments if one is interested in extrapolating results to the general population. This paper notes that there is an isomorphism between the Roy model for the sorting of workers into sectors and the decision of subjects to participate in randomized experiments. The main implication is that, as the probability of receiving active treatment rises, patients who are less optimistic about new treatment will begin to enroll and estimates of treatment effects will fall. This, in turn, implies that selection bias is positive. These findings are confirmed with data from trials of ulcer medications.

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  • Malani, Anup, 2008. "Patient enrollment in medical trials: Selection bias in a randomized experiment," Journal of Econometrics, Elsevier, vol. 144(2), pages 341-351, June.
    • Handle: RePEc:eee:econom:v:144:y:2008:i:2:p:341-351
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    1. James J. Heckman & Jeffrey A. Smith, 1995. "Assessing the Case for Social Experiments," Journal of Economic Perspectives, American Economic Association, vol. 9(2), pages 85-110, Spring.
    2. Tomas Philipson, 1999. "External Treatment Effects and Program Implementation Bias," Working Papers 9929, Harris School of Public Policy Studies, University of Chicago.
    3. Heckman, James J & Honore, Bo E, 1990. "The Empirical Content of the Roy Model," Econometrica, Econometric Society, vol. 58(5), pages 1121-1149, September.
    4. Hadar, Josef & Russell, William R, 1969. "Rules for Ordering Uncertain Prospects," American Economic Review, American Economic Association, vol. 59(1), pages 25-34, March.
    5. Heckman, James J, 1996. "Randomization as an Instrumental Variable: Notes," The Review of Economics and Statistics, MIT Press, vol. 78(2), pages 336-341, May.
    6. A. D. Roy, 1951. "Some Thoughts On The Distribution Of Earnings," Oxford Economic Papers, Oxford University Press, vol. 3(2), pages 135-146.
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    Cited by:

    1. Seth M. Freedman & Daniel W. Sacks & Kosali I. Simon & Coady Wing, 2022. "Direct and indirect effects of vaccines: Evidence from COVID-19," NBER Working Papers 30550, National Bureau of Economic Research, Inc.
    2. 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.
    3. Belot, Michèle & James, Jonathan, 2014. "A new perspective on the issue of selection bias in randomized controlled field experiments," Economics Letters, Elsevier, vol. 124(3), pages 326-328.
    4. Basu, Anirban, 2015. "Welfare implications of learning through solicitation versus diversification in health care," Journal of Health Economics, Elsevier, vol. 42(C), pages 165-173.
    5. Malani, Anup & Philipson, Tomas J., 2011. "Can Medical Progress be Sustained? Implications of the Link Between Development and Output Markets," Working Papers 237, The University of Chicago Booth School of Business, George J. Stigler Center for the Study of the Economy and the State.
    6. Belot, Michèle & James, Jonathan, 2016. "Partner selection into policy relevant field experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 123(C), pages 31-56.
    7. 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.
    8. Utteeyo Dasgupta & Lata Gangadharan & Pushkar Maitra & Subha Mani & Samyukta Subramanian, 2012. "Choosing to be Trained: Evidence from a Field Experiment," Monash Economics Working Papers 43-12, Monash University, Department of Economics.
    9. 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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