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Balancing the elicitation burden and the richness of expert input when quantifying discrete Bayesian networks

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Barons, Martine J., Mascaro, Steven and Hanea, Anca (2022) Balancing the elicitation burden and the richness of expert input when quantifying discrete Bayesian networks. Risk Analysis, 42 (6). pp. 1196-1234. doi:10.1111/risa.13772

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Official URL: https://doi.org/10.1111/risa.13772

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Abstract

Structured expert judgment (SEJ) is a method for obtaining estimates of uncertain quantities from groups of experts in a structured way designed to minimize the pervasive cognitive frailties of unstructured approaches. When the number of quantities required is large, the burden on the groups of experts is heavy, and resource constraints may mean that eliciting all the quantities of interest is impossible. Partial elicitations can be complemented with imputation methods for the remaining, unelicited quantities. In the case where the quantities of interest are conditional probability distributions, the natural relationship between the quantities can be exploited to impute missing probabilities. Here we test the Bayesian intelligence interpolation method and its variations for Bayesian network conditional probability tables, called “InterBeta.” We compare the various outputs of InterBeta on two cases where conditional probability tables were elicited from groups of experts. We show that interpolated values are in good agreement with experts' values and give guidance on how InterBeta could be used to good effect to reduce expert burden in SEJ exercises.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science, Engineering and Medicine > Science > Statistics
Library of Congress Subject Headings (LCSH): Bayesian statistical decision theory, Multilevel models (Statistics), Decision making -- Mathematical models
Journal or Publication Title: Risk Analysis
Publisher: Wiley-Blackwell Publishing Ltd.
ISSN: 0272-4332
Official Date: June 2022
Dates:
DateEvent
June 2022Published
19 June 2021Available
Volume: 42
Number: 6
Page Range: pp. 1196-1234
DOI: 10.1111/risa.13772
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
EP/K039628/1[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
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