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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/21596

Title: Probability elicitation under severe time pressure: a rank-based method
Authors: Jaspersen, Johannes G.
Montibeller, Gilberto
Keywords: Emerging threats
Maximum entropy
Ordinal information
Probabilistic risk analysis
Probability elicitation
Issue Date: 2015
Publisher: Wiley / © Society for Risk Analysis
Citation: JASPERSEN, J. and MONTIBELLER, G., 2015. Probability elicitation under severe time pressure: a rank-based method. Risk Analysis, 35 (7), pp. 1317 - 1335.
Abstract: Probability elicitation protocols are used to assess and incorporate subjective probabilities in risk and decision analysis. While most of these protocols use methods that have focused on the precision of the elicited probabilities, the speed of the elicitation process has often been neglected. However, speed is also important, particularly when experts need to examine a large number of events on a recurrent basis. Furthermore, most existing elicitation methods are numerical in nature, but there are various reasons why an expert would refuse to give such precise ratio-scale estimates, even if highly numerate. This may occur, for instance, when there is lack of sufficient hard evidence, when assessing very uncertain events (such as emergent threats), or when dealing with politicized topics (such as terrorism or disease outbreaks). In this article, we adopt an ordinal ranking approach from multicriteria decision analysis to provide a fast and nonnumerical probability elicitation process. Probabilities are subsequently approximated from the ranking by an algorithm based on the principle of maximum entropy, a rule compatible with the ordinal information provided by the expert. The method can elicit probabilities for a wide range of different event types, including new ways of eliciting probabilities for stochastically independent events and low-probability events. We use a Monte Carlo simulation to test the accuracy of the approximated probabilities and try the method in practice, applying it to a real-world risk analysis recently conducted for DEFRA (the U.K. Department for the Environment, Farming and Rural Affairs): the prioritization of animal health threats.
Description: This paper is closed access.
Version: Published
DOI: 10.1111/risa.12357
URI: https://dspace.lboro.ac.uk/2134/21596
Publisher Link: http://dx.doi.org/10.1111/risa.12357
ISSN: 0272-4332
Appears in Collections:Closed Access (Business School)

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