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A New Measure of Attributable Risk for Public Health Applications

Author

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  • Louis A. Cox, Jr.

    (Arthur D. Little, Inc., 35 Acorn Park, Cambridge, Massachusetts 02140 and Operations Research Center, E40, Massachusetts Institute of Technology, Cambridge, Massachusetts 02138)

Abstract

A persistent conceptual problem in the theory of risk accounting and risk analysis methodology is that of allocating or attributing a risk among the joint causes or "factors" producing it. When multiple factors interact, the especially difficult problem of "risk externalities" arises. Drawing on related work in the mathematical theory of games that seeks solutions to similar philosophical and conceptual problems, this paper proposes a method for solving the risk attribution problem. The proposed solution is justified on the grounds that it is the unique risk attribution function satisfying three reasonable principles, or "axioms," of risk accounting. A mathematical framework for formulating risk attribution problems, and several possible applications, are also discussed.

Suggested Citation

  • Louis A. Cox, Jr., 1985. "A New Measure of Attributable Risk for Public Health Applications," Management Science, INFORMS, vol. 31(7), pages 800-813, July.
    • Handle: RePEc:inm:ormnsc:v:31:y:1985:i:7:p:800-813
    DOI: 10.1287/mnsc.31.7.800
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    Citations

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    Cited by:

    1. Ricardo Martínez & Joaquín Sánchez-Soriano, 2021. "Mathematical indices for the influence of risk factors on the lethality of a disease," ThE Papers 21/02, Department of Economic Theory and Economic History of the University of Granada..
    2. Louis Anthony (Tony) Cox & Edward Sanders, 2006. "Estimating Preventable Fractions of Disease Caused by a Specified Biological Mechanism: PAHs in Smoking Lung Cancers as an Example," Risk Analysis, John Wiley & Sons, vol. 26(4), pages 881-892, August.
    3. Oskar Skibski & Tomasz Michalak, 2020. "Fair division in the presence of externalities," International Journal of Game Theory, Springer;Game Theory Society, vol. 49(1), pages 147-172, March.
    4. Retzer, J.J. & Soofi, E.S. & Soyer, R., 2009. "Information importance of predictors: Concept, measures, Bayesian inference, and applications," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2363-2377, April.
    5. Louis Anthony Cox, 1987. "Statistical Issues in the Estimation of Assigned Shares for Carcinogenesis Liability," Risk Analysis, John Wiley & Sons, vol. 7(1), pages 71-80, March.
    6. Bertram Price & Michael MacNicoll, 2015. "Multiple Interacting Risk Factors: On Methods for Allocating Risk Factor Interactions," Risk Analysis, John Wiley & Sons, vol. 35(5), pages 931-940, May.
    7. Fritz A. Seiler, 1986. "Assigned Shares and Combined Insults," Risk Analysis, John Wiley & Sons, vol. 6(3), pages 371-372, September.
    8. Jonathan B. Wiener, 2020. "Learning to Manage the Multirisk World," Risk Analysis, John Wiley & Sons, vol. 40(S1), pages 2137-2143, November.
    9. Razia Azen & Nicole Traxel, 2009. "Using Dominance Analysis to Determine Predictor Importance in Logistic Regression," Journal of Educational and Behavioral Statistics, , vol. 34(3), pages 319-347, September.

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