IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v16y1996i4p399-403.html
   My bibliography  Save this article

Do Violations of the Axioms of Expected Utility Theory Threaten Decision Analysis?

Author

Listed:
  • Robert F. Nease JR

Abstract

Research demonstrates that people violate the independence principle of expected utility theory, raising the question of whether expected utility theory is normative for medical decision making. The author provides three arguments that violations of the independence principle are less problematic than they might first appear. First, the independence principle follows from other more fundamental axioms whose appeal may be more readily apparent than that of the independence principle. Second, the axioms need not be descriptive to be normative, and they need not be attractive to all decision makers for expected utility theory to be useful for some. Finally, by providing a metaphor of decision analysis as a conversation between the actual decision maker and a model decision maker, the author argues that expected utility theory need not be purely normative for decision analysis to be useful. In short, violations of the in dependence principle do not necessarily represent direct violations of the axioms of expected utility theory; behavioral violations of the axioms of expected utility theory do not necessarily imply that decision analysis is not normative; and full normativeness is not necessary for decision analysis to generate valuable insights. Key words: ex pected utility theory; independence axiom; decision analysis; normativeness. (Med De cis Making 1996;16:399-403)

Suggested Citation

  • Robert F. Nease JR, 1996. "Do Violations of the Axioms of Expected Utility Theory Threaten Decision Analysis?," Medical Decision Making, , vol. 16(4), pages 399-403, October.
  • Handle: RePEc:sae:medema:v:16:y:1996:i:4:p:399-403
    DOI: 10.1177/0272989X9601600410
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X9601600410
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0272989X9601600410?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ross D. Shachter, 1986. "Evaluating Influence Diagrams," Operations Research, INFORMS, vol. 34(6), pages 871-882, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Leslie A. Lenert & Jonathan R. Treadwell, 1999. "Effects on Preferences of Violations of Procedural Invariance," Medical Decision Making, , vol. 19(4), pages 473-481, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bielza, Concha & Gómez, Manuel & Shenoy, Prakash P., 2011. "A review of representation issues and modeling challenges with influence diagrams," Omega, Elsevier, vol. 39(3), pages 227-241, June.
    2. Zitrou, Athena & Bedford, Tim & Walls, Lesley, 2010. "Bayes geometric scaling model for common cause failure rates," Reliability Engineering and System Safety, Elsevier, vol. 95(2), pages 70-76.
    3. Tan, Kim Hua & Zhan, YuanZhu & Ji, Guojun & Ye, Fei & Chang, Chingter, 2015. "Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph," International Journal of Production Economics, Elsevier, vol. 165(C), pages 223-233.
    4. Prakash Shenoy, 1998. "Game Trees For Decision Analysis," Theory and Decision, Springer, vol. 44(2), pages 149-171, April.
    5. Oepping, Hardy, 2016. "Ein Bayes-Netz zur Analyse des Absturzrisikos im Gerüstbau [A Bayesian network for analysing the risk of falling from height in scaffolding]," MPRA Paper 73602, University Library of Munich, Germany.
    6. Borgonovo, Emanuele & Tonoli, Fabio, 2014. "Decision-network polynomials and the sensitivity of decision-support models," European Journal of Operational Research, Elsevier, vol. 239(2), pages 490-503.
    7. Bensi, Michelle & Kiureghian, Armen Der & Straub, Daniel, 2013. "Efficient Bayesian network modeling of systems," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 200-213.
    8. Groth, Katrina M. & Smith, Reuel & Moradi, Ramin, 2019. "A hybrid algorithm for developing third generation HRA methods using simulator data, causal models, and cognitive science," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    9. Vic Hasselblad & Douglas C. McCrory, 1995. "Meta-analytic Tools for Medical Decision Making: A Practical Guide," Medical Decision Making, , vol. 15(1), pages 81-96, February.
    10. Concha Bielza & Prakash P. Shenoy, 1999. "A Comparison of Graphical Techniques for Asymmetric Decision Problems," Management Science, INFORMS, vol. 45(11), pages 1552-1569, November.
    11. Thwaites, Peter A. & Smith, Jim Q., 2018. "A graphical method for simplifying Bayesian games," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 3-11.
    12. Stephen G. Pauker & John B. Wong, 2005. "The Influence of Influence Diagrams in Medicine," Decision Analysis, INFORMS, vol. 2(4), pages 238-244, December.
    13. Barry R. Cobb, 2007. "Influence Diagrams with Continuous Decision Variables and Non-Gaussian Uncertainties," Decision Analysis, INFORMS, vol. 4(3), pages 136-155, September.
    14. Debarun Bhattacharjya & Ross D. Shachter, 2012. "Formulating Asymmetric Decision Problems as Decision Circuits," Decision Analysis, INFORMS, vol. 9(2), pages 138-145, June.
    15. Misuri, Alessio & Khakzad, Nima & Reniers, Genserik & Cozzani, Valerio, 2019. "A Bayesian network methodology for optimal security management of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    16. Sättele, Martina & Bründl, Michael & Straub, Daniel, 2015. "Reliability and effectiveness of early warning systems for natural hazards: Concept and application to debris flow warning," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 192-202.
    17. Özgür-Ünlüakın, Demet & Bilgiç, Taner, 2017. "Performance analysis of an aggregation and disaggregation solution procedure to obtain a maintenance plan for a partially observable multi-component system," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 652-662.
    18. Koller, Daphne & Milch, Brian, 2003. "Multi-agent influence diagrams for representing and solving games," Games and Economic Behavior, Elsevier, vol. 45(1), pages 181-221, October.
    19. David Rios Insua & Aitor Couce‐Vieira & Jose A. Rubio & Wolter Pieters & Katsiaryna Labunets & Daniel G. Rasines, 2021. "An Adversarial Risk Analysis Framework for Cybersecurity," Risk Analysis, John Wiley & Sons, vol. 41(1), pages 16-36, January.
    20. Concha Bielza & Peter Müller & David Ríos Insua, 1999. "Decision Analysis by Augmented Probability Simulation," Management Science, INFORMS, vol. 45(7), pages 995-1007, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:medema:v:16:y:1996:i:4:p:399-403. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.