Literature DB >> 33629402

Uncertainty Quantification with Experts: Present Status and Research Needs.

Anca M Hanea1, Victoria Hemming2, Gabriela F Nane3.   

Abstract

Expert elicitation is deployed when data are absent or uninformative and critical decisions must be made. In designing an expert elicitation, most practitioners seek to achieve best practice while balancing practical constraints. The choices made influence the required time and effort investment, the quality of the elicited data, experts' engagement, the defensibility of results, and the acceptability of resulting decisions. This piece outlines some of the common choices practitioners encounter when designing and conducting an elicitation. We discuss the evidence supporting these decisions and identify research gaps. This will hopefully allow practitioners to better navigate the literature, and will inspire the expert judgment research community to conduct well powered, replicable experiments that properly address the research gaps identified.
© 2021 Society for Risk Analysis.

Entities:  

Keywords:  CM; IDEA; SHELF; expert elicitation protocols; uncertainty quantification

Mesh:

Year:  2021        PMID: 33629402     DOI: 10.1111/risa.13718

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  3 in total

1.  Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling.

Authors:  Ben Swallow; Paul Birrell; Joshua Blake; Mark Burgman; Peter Challenor; Luc E Coffeng; Philip Dawid; Daniela De Angelis; Michael Goldstein; Victoria Hemming; Glenn Marion; Trevelyan J McKinley; Christopher E Overton; Jasmina Panovska-Griffiths; Lorenzo Pellis; Will Probert; Katriona Shea; Daniel Villela; Ian Vernon
Journal:  Epidemics       Date:  2022-02-10       Impact factor: 4.396

2.  Self-Reporting of Risk Pathways and Parameter Values for Foot-and-Mouth Disease in Slaughter Cattle from Alternative Production Systems by Kenyan and Ugandan Veterinarians.

Authors:  Julie Adamchick; Karl M Rich; Andres M Perez
Journal:  Viruses       Date:  2021-10-20       Impact factor: 5.048

3.  Co-designing and building an expert-elicited non-parametric Bayesian network model: demonstrating a methodology using a Bonamia Ostreae spread risk case study.

Authors:  Anca M Hanea; Zoë Hilton; Ben Knight; Andrew P Robinson
Journal:  Risk Anal       Date:  2022-02-20       Impact factor: 4.302

  3 in total

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