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The effect of the number of seed variables on the performance of Cooke′s classical model

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  • Eggstaff, Justin W.
  • Mazzuchi, Thomas A.
  • Sarkani, Shahram

Abstract

In risk analysis, Cooke′s classical model for aggregating expert judgment has been widely used for over 20 years. However, the validity of this model has been the subject of much debate. Critics assert that this model′s scoring rule may unintentionally reward experts who manipulate their quantile estimates in order to receive a greater weight. In addition, the question of the number of seed variables required to ensure adequate performance of Cooke′s classical model remains unanswered. In this study, we conduct a comprehensive examination of the model through an iterative, cross validation test to perform an out-of-sample comparison between Cooke′s classical model and the equal-weight linear opinion pool method on almost all of the expert judgment studies compiled by Cooke and colleagues to date. Our results indicate that Cooke′s classical model significantly outperforms equally weighting expert judgment, regardless of the number of seed variables used; however, there may, in fact, be a maximum number of seed variables beyond which Cooke′s model cannot outperform an equally-weighted panel.

Suggested Citation

  • Eggstaff, Justin W. & Mazzuchi, Thomas A. & Sarkani, Shahram, 2014. "The effect of the number of seed variables on the performance of Cooke′s classical model," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 72-82.
  • Handle: RePEc:eee:reensy:v:121:y:2014:i:c:p:72-82
    DOI: 10.1016/j.ress.2013.07.015
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    1. James K. Hammitt & Yifan Zhang, 2013. "Combining Experts’ Judgments: Comparison of Algorithmic Methods Using Synthetic Data," Risk Analysis, John Wiley & Sons, vol. 33(1), pages 109-120, January.
    2. Flandoli, F. & Giorgi, E. & Aspinall, W.P. & Neri, A., 2011. "Comparison of a new expert elicitation model with the Classical Model, equal weights and single experts, using a cross-validation technique," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1292-1310.
    3. Stephen C. Hora, 2004. "Probability Judgments for Continuous Quantities: Linear Combinations and Calibration," Management Science, INFORMS, vol. 50(5), pages 597-604, May.
    4. R. Winkler & Javier Muñoz & José Cervera & José Bernardo & Gail Blattenberger & Joseph Kadane & Dennis Lindley & Allan Murphy & Robert Oliver & David Ríos-Insua, 1996. "Scoring rules and the evaluation of probabilities," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 5(1), pages 1-60, June.
    5. Victor Richmond R. Jose & Robert L. Winkler, 2009. "Evaluating Quantile Assessments," Operations Research, INFORMS, vol. 57(5), pages 1287-1297, October.
    6. Lin, Shi-Woei & Bier, Vicki M., 2008. "A study of expert overconfidence," Reliability Engineering and System Safety, Elsevier, vol. 93(5), pages 711-721.
    7. 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.
    8. Garthwaite, Paul H. & Kadane, Joseph B. & O'Hagan, Anthony, 2005. "Statistical Methods for Eliciting Probability Distributions," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 680-701, June.
    9. Norman Dalkey & Olaf Helmer, 1963. "An Experimental Application of the DELPHI Method to the Use of Experts," Management Science, INFORMS, vol. 9(3), pages 458-467, April.
    10. Robert L. Winkler, 1968. "The Consensus of Subjective Probability Distributions," Management Science, INFORMS, vol. 15(2), pages 61-75, October.
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    Citations

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    Cited by:

    1. Bolger, Fergus & Wright, George, 2017. "Use of expert knowledge to anticipate the future: Issues, analysis and directions," International Journal of Forecasting, Elsevier, vol. 33(1), pages 230-243.
    2. Colson, Abigail R. & Cooke, Roger M., 2017. "Cross validation for the classical model of structured expert judgment," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 109-120.
    3. Rongen, G. & Morales-Nápoles, O. & Kok, M., 2022. "Expert judgment-based reliability analysis of the Dutch flood defense system," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    4. Bolger, Donnacha & Houlding, Brett, 2017. "Deriving the probability of a linear opinion pooling method being superior to a set of alternatives," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 41-49.
    5. Patrick Afflerbach & Christopher Dun & Henner Gimpel & Dominik Parak & Johannes Seyfried, 2021. "A Simulation-Based Approach to Understanding the Wisdom of Crowds Phenomenon in Aggregating Expert Judgment," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(4), pages 329-348, August.
    6. Li, Yaxin & Ding, Yuxin & Guo, Yuliang & Cui, Haizhou & Gao, Haiyi & Zhou, Ziyu & (Aaron) Zhang, Nanbo & Zhu, Siyao & Chen, Faan, 2023. "An integrated decision model with reliability to support transport safety system analysis," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    7. Cooke, Roger M. & Marti, Deniz & Mazzuchi, Thomas, 2021. "Expert forecasting with and without uncertainty quantification and weighting: What do the data say?," International Journal of Forecasting, Elsevier, vol. 37(1), pages 378-387.

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