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Elicitator : an expert elicitation tool for regression in ecology

James, Allan, Low Choy, Samantha, & Mengersen, Kerrie L. (2010) Elicitator : an expert elicitation tool for regression in ecology. Environmental Modelling & Software, 25(1), pp. 129-145.

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Abstract

Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited, or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior model in Bayesian regression. Potential environmental domains for applying this elicitation tool include habitat modeling, assessing detectability or eradication, ecological condition assessments, risk analysis, and quantifying inputs to complex models of ecological processes. The tool has been developed to be user-friendly, extensible, and facilitate consistent and repeatable elicitation of expert knowledge across these various domains. We demonstrate its application to elicitation for logistic regression in a geographically based ecological context. The underlying statistical methodology is also novel, utilizing an indirect elicitation approach to target expert knowledge on a case-by-case basis. For several elicitation sites (or cases), experts are asked simply to quantify their estimated ecological response (e.g. probability of presence), and its range of plausible values, after inspecting (habitat) covariates via GIS.

Impact and interest:

23 citations in Scopus
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20 citations in Web of Science®

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ID Code: 30011
Item Type: Journal Article
Keywords: Elicitation software, Expert elicitation, Expert opinion, Bayesian statistics, Regression, Ecology, Java
DOI: 10.1016/j.envsoft.2009.07.003
ISSN: 1364-8152
Divisions: Current > Schools > School of Curriculum
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Current > Research Centres > High Performance Computing and Research Support
Past > Schools > Mathematical Sciences
Copyright Owner: Copyright 2009 Elsevier Ltd. All rights reserved.
Deposited On: 28 Jan 2010 12:11
Last Modified: 25 Mar 2013 18:10

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