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A comparison of prior elicitation aggregation using the classical method and SHELF

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  • Cameron J. Williams
  • Kevin J. Wilson
  • Nina Wilson

Abstract

Subjective Bayesian prior distributions elicited from experts can be aggregated together to form group priors. This paper compares aggregated priors formed by equal weight aggregation, the classical method and the Sheffield elicitation framework to each other and individual expert priors, using an expert elicitation carried out for a clinical trial. Aggregation methods and individual expert prior distributions are compared using proper scoring rules to compare the informativeness and calibration of the distributions. The three aggregation methods outperform the individual experts, and the Sheffield elicitation framework performs best among them.

Suggested Citation

  • Cameron J. Williams & Kevin J. Wilson & Nina Wilson, 2021. "A comparison of prior elicitation aggregation using the classical method and SHELF," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 920-940, July.
    • Handle: RePEc:bla:jorssa:v:184:y:2021:i:3:p:920-940
    DOI: 10.1111/rssa.12691
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    References listed on IDEAS

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    5. John Paul Gosling, 2018. "SHELF: The Sheffield Elicitation Framework," International Series in Operations Research & Management Science, in: Luis C. Dias & Alec Morton & John Quigley (ed.), Elicitation, chapter 0, pages 61-93, Springer.
    6. 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.
    7. 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.
    8. John Quigley & Abigail Colson & Willy Aspinall & Roger M. Cooke, 2018. "Elicitation in the Classical Model," International Series in Operations Research & Management Science, in: Luis C. Dias & Alec Morton & John Quigley (ed.), Elicitation, chapter 0, pages 15-36, Springer.
    9. Ine H. J. Van Der Fels‐Klerx & Louis H. J. Goossens & Helmut W. Saatkamp & Suzan H. S. Horst, 2002. "Elicitation of Quantitative Data from a Heterogeneous Expert Panel: Formal Process and Application in Animal Health," Risk Analysis, John Wiley & Sons, vol. 22(1), pages 67-81, February.
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    Cited by:

    1. Julia R. Falconer & Eibe Frank & Devon L. L. Polaschek & Chaitanya Joshi, 2022. "Methods for Eliciting Informative Prior Distributions: A Critical Review," Decision Analysis, INFORMS, vol. 19(3), pages 189-204, September.
    2. Williamson, S. Faye & Jacko, Peter & Jaki, Thomas, 2022. "Generalisations of a Bayesian decision-theoretic randomisation procedure and the impact of delayed responses," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).

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