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TU Delft expert judgment data base

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  • Cooke, Roger M.
  • Goossens, Louis L.H.J.

Abstract

We review the applications of structured expert judgment uncertainty quantification using the “classical model†developed at the Delft University of Technology over the last 17 years [Cooke RM. Experts in uncertainty. Oxford: Oxford University Press; 1991; Expert judgment study on atmospheric dispersion and deposition. Report Faculty of Technical Mathematics and Informatics No.01-81, Delft University of Technology; 1991]. These involve 45 expert panels, performed under contract with problem owners who reviewed and approved the results. With a few exceptions, all these applications involved the use of seed variables; that is, variables from the experts’ area of expertise for which the true values are available post hoc. Seed variables are used to (1) measure expert performance, (2) enable performance-based weighted combination of experts’ distributions, and (3) evaluate and hopefully validate the resulting combination or “decision maker†. This article reviews the classical model for structured expert judgment and the performance measures, reviews applications, comparing performance-based decision makers with “equal weight†decision makers, and collects some lessons learned.

Suggested Citation

  • Cooke, Roger M. & Goossens, Louis L.H.J., 2008. "TU Delft expert judgment data base," Reliability Engineering and System Safety, Elsevier, vol. 93(5), pages 657-674.
    • Handle: RePEc:eee:reensy:v:93:y:2008:i:5:p:657-674
    DOI: 10.1016/j.ress.2007.03.005
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    References listed on IDEAS

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    1. L.H.J. Goossens & R.M. Cooke & F Woudenberg & P Van Der Torn, 1998. "Expert judgement and lethal toxicity of inhaled chemicals," Journal of Risk Research, Taylor & Francis Journals, vol. 1(2), pages 117-133, April.
    2. Arno Willems & Mart Janssen ** & Chris Verstegen ** & Tim Bedford, 2005. "Expert quantification of uncertainties in a risk analysis for an infrastructure project," Journal of Risk Research, Taylor & Francis Journals, vol. 8(1), pages 3-17, January.
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    4. Robert L. Winkler & Thomas S. Wallsten & Ronald G. Whitfield & Harvey M. Richmond & Stanley R. Hayes & Arlene S. Rosenbaum, 1995. "An Assessment of the Risk of Chronic Lung Injury Attributable to Long-Term Ozone Exposure," Operations Research, INFORMS, vol. 43(1), pages 19-28, February.
    5. Du, C. & Kurowicka, D. & Cooke, R.M., 2006. "Techniques for generic probabilistic inversion," Computational Statistics & Data Analysis, Elsevier, vol. 50(5), pages 1164-1187, March.
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