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Explaining Distortions in Utility Elicitation through the Rank-dependent Model for Risky Choices

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  • Peter Wakker
  • Anne Stiggelbout

Abstract

The standard-gamble (SG) method has been accepted as the "gold standard" for the elic itation of utility when risk or uncertainty is involved in decisions, and thus for the measurement of utility in medical decisions. It is based on the assumptions of expected-utility theory. Unfortunately, there is now abundant evidence that expected utility is not empirically valid, and that the SG method overestimates risk aversion and the utilities of impaired health states. This paper shows how rank-dependent utility theory, a newly developed theory in decision science, can explain the main violations of expected utility. Thus it provides a means for correcting the SG method and for improving the assessments of quality-adjusted life years for medical decisions in which there is uncertainty about outcomes. Key words: health- state utility; risk aversion; rank dependence; medical decision making; standard gamble. (Med Decis Making 1995;15:180-186)

Suggested Citation

  • Peter Wakker & Anne Stiggelbout, 1995. "Explaining Distortions in Utility Elicitation through the Rank-dependent Model for Risky Choices," Medical Decision Making, , vol. 15(2), pages 180-186, June.
    • Handle: RePEc:sae:medema:v:15:y:1995:i:2:p:180-186
    DOI: 10.1177/0272989X9501500212
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    References listed on IDEAS

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    Cited by:

    1. Oliver, Adam, 2003. "The internal consistency of the standard gamble: tests after adjusting for prospect theory," LSE Research Online Documents on Economics 159, London School of Economics and Political Science, LSE Library.
    2. Attema, Arthur E. & Brouwer, Werner B.F. & l’Haridon, Olivier, 2013. "Prospect theory in the health domain: A quantitative assessment," Journal of Health Economics, Elsevier, vol. 32(6), pages 1057-1065.
    3. Adam Oliver, 2003. "Testing rank‐dependent utility theory for health outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 12(10), pages 863-871, October.
    4. Han Bleichrodt & Jose Luis Pinto, 2000. "A Parameter-Free Elicitation of the Probability Weighting Function in Medical Decision Analysis," Management Science, INFORMS, vol. 46(11), pages 1485-1496, November.
    5. Han Bleichrodt & José Luis Pinto, 2000. "An experimental test of loss aversion and scale compatibility," Working Papers, Research Center on Health and Economics 467, Department of Economics and Business, Universitat Pompeu Fabra.
    6. Han Bleichrodt & Jose Luis Pinto & Peter P. Wakker, 2001. "Making Descriptive Use of Prospect Theory to Improve the Prescriptive Use of Expected Utility," Management Science, INFORMS, vol. 47(11), pages 1498-1514, November.
    7. Louis Eeckhoudt, 1996. "Expected Utility Theory—Is It Normative or Simply "Practical"?," Medical Decision Making, , vol. 16(1), pages 12-13, February.
    8. Arthur E. Attema & Werner B.F. Brouwer, 2014. "Deriving Time Discounting Correction Factors For Tto Tariffs," Health Economics, John Wiley & Sons, Ltd., vol. 23(4), pages 410-425, April.
    9. Joshua A. Salomon & Christopher J.L. Murray, 2004. "A multi‐method approach to measuring health‐state valuations," Health Economics, John Wiley & Sons, Ltd., vol. 13(3), pages 281-290, March.
    10. Ahmed M. Bayoumi & Donald A. Redelmeier, 2000. "Decision Analysis with Cumulative Prospect Theory," Medical Decision Making, , vol. 20(4), pages 404-411, October.
    11. Doctor, Jason N. & Bleichrodt, Han & Miyamoto, John & Temkin, Nancy R. & Dikmen, Sureyya, 2004. "A new and more robust test of QALYs," Journal of Health Economics, Elsevier, vol. 23(2), pages 353-367, March.
    12. Kristian Schultz Hansen & Lars Peter Østerdal, 2006. "Models of Quality‐Adjusted Life Years when Health Varies Over Time: Survey and Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 20(2), pages 229-255, April.
    13. Valerie Seror, 2008. "Fitting observed and theoretical choices – women's choices about prenatal diagnosis of Down syndrome," Health Economics, John Wiley & Sons, Ltd., vol. 17(5), pages 557-577, May.
    14. Oliver, Adam, 2003. "The internal consistency of the standard gamble: tests after adjusting for prospect theory," Journal of Health Economics, Elsevier, vol. 22(4), pages 659-674, July.
    15. Stefan Felder, 2022. "Decision thresholds with genetic testing," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(6), pages 1071-1078, August.
    16. Stefan A. Lipman & Werner B.F. Brouwer & Arthur E. Attema, 2019. "QALYs without bias? Nonparametric correction of time trade‐off and standard gamble weights based on prospect theory," Health Economics, John Wiley & Sons, Ltd., vol. 28(7), pages 843-854, July.
    17. Magnus Johannesson & Bengt Jönsson & Göran Karlsson, 1996. "Outcome measurement in economic evaluation," Health Economics, John Wiley & Sons, Ltd., vol. 5(4), pages 279-296, July.
    18. Han Bleichrodt, 2002. "A new explanation for the difference between time trade‐off utilities and standard gamble utilities," Health Economics, John Wiley & Sons, Ltd., vol. 11(5), pages 447-456, July.
    19. Kristian Schultz Hansen & Lars Peter Østerdal, 2004. "QALYs When Health Varies Over Time: An Analysis of Model Identification and Parameter Estimation from Time Trade-Off and Standard Gamble Scores," Discussion Papers 04-05, University of Copenhagen. Department of Economics.
    20. Lisa Prosser & James Hammitt & Ron Keren, 2007. "Measuring Health Preferences for Use in Cost-Utility and Cost-Benefit Analyses of Interventions in Children," PharmacoEconomics, Springer, vol. 25(9), pages 713-726, September.
    21. Oliver, Adam, 2003. "A quantitative and qualitative test of the Allais paradox using health outcomes," Journal of Economic Psychology, Elsevier, vol. 24(1), pages 35-48, February.
    22. Sylvie M. C. van Osch & Anne M. Stiggelbout, 2008. "The construction of standard gamble utilities," Health Economics, John Wiley & Sons, Ltd., vol. 17(1), pages 31-40, January.

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