A Bayes Linear Approach to Weight-of-Evidence Risk Assessment for Skin Allergy

Gosling, John Paul; Hart, Andy; Owen, Helen; Davies, Michael J.; Jin, Li; MacKay, Cameron

doi:10.1214/13-ba807

Cited by 18 publications

(10 citation statements)

References 6 publications

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“…( 2013 ) described a wide range of approaches, ranging from those that are largely qualitative in nature (e.g., Guyatt et al. 2011a ) to fully quantitative techniques (e.g., Gosling et al. 2013 ).…”

Section: Introductionmentioning

confidence: 99%

Weight of Evidence for Hazard Identification: A Critical Review of the Literature

Martin

Bladier

Meek

et al. 2018

Environ Health Perspect

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Background:Transparency when documenting and assessing weight of evidence (WOE) has been an area of increasing focus for national and international health agencies.Objective:The objective of this work was to conduct a critical review of WOE analysis methods as a basis for developing a practical framework for considering and assessing WOE in hazard identification in areas of application at the French Agency for Food, Environmental and Occupational Health and Safety (ANSES).Methods:Based on a review of the literature and directed requests to 63 international and national agencies, 116 relevant articles and guidance documents were selected. The WOE approaches were assessed based on three aspects: the extent of their prescriptive nature, their purpose-specific relevance, and their ease of implementation.Results:Twenty-four approaches meeting the specified criteria were identified from selected reviewed documents. Most approaches satisfied one or two of the assessed considerations, but not all three. The approaches were grouped within a practical framework comprising the following four stages: (1) planning the assessment, including scoping, formulating the question, and developing the assessment method; (2) establishing lines of evidence (LOEs), including identifying and selecting studies, assessing their quality, and integrating with studies of similar type; (3) integrating the LOEs to evaluate WOE; and (4) presenting conclusions.Discussion:Based on the review, considerations for selecting methods for a wide range of applications are proposed. Priority areas for further development are identified. https://doi.org/10.1289/EHP3067

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Section: Introductionmentioning

confidence: 99%

Weight of Evidence for Hazard Identification: A Critical Review of the Literature

Martin

Bladier

Meek

et al. 2018

Environ Health Perspect

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“…Direct correlation and adjusted ex-910 pectation barely showed any differences for experts' performance. However, over 15% of the responses were deemed inconsistent.While this is the first and only such complete attempt to explicitly focus on the actual elicitation of covariance 915 in BLM, some main references for empirical studies with documented expert judgment approaches areGosling et al (2013),Revie et al (2011), Bedford et al (2008), Farrow et al (1997) and O'Hagan et al (1992.…”

mentioning

confidence: 99%

Expert judgement for dependence in probabilistic modelling: A systematic literature review and future research directions

Werner

Bedford

Cooke

et al. 2017

European Journal of Operational Research

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Many applications in decision making under uncertainty and probabilistic risk assessment require the assessment of multiple, dependent uncertain quantities, so that in addition to marginal distributions, interdependence needs to be modelled in order to properly understand the overall risk. Nevertheless, relevant historical data on dependence information are often not available or simply too costly to obtain. In this case, the only sensible option is to elicit this uncertainty through the use of expert judgements. In expert judgement studies, a structured approach to eliciting variables of interest is desirable so that their assessment is methodologically robust. One of the key decisions during the elicitation process is the form in which the uncertainties are elicited. This choice is subject to various, potentially conflicting, desiderata related to e.g. modelling convenience, coherence between elicitation parameters and the model, combining judgements, and the assessment burden for the experts. While extensive and systematic guidance to address these considerations exists for single variable uncertainty elicitation, for higher dimensions very little such guidance is available. Therefore this paper offers a systematic review of the current literature on eliciting dependence. The literature on the elicitation of dependence parameters such as correlations is presented alongside commonly used dependence models and experience from case studies. From this, guidance about the strategy for dependence assessment is given and gaps in the existing research are identified to determine future directions for structured methods to elicit dependence. (Anca M. Hanea), O.MoralesNapoles@tudelft.nl (Oswaldo Morales-Nápoles) cause variables in the model are correlated, or indirectly when an uncertainty analysis of model parameters is carried out to explore model robustness. Both cases exhibit complex interrelations and dependencies which need to be considered if assumptions such as independence are not 10 justifiable.However, it is often not straightforward to either model or quantify dependence. In particular whenever no relevant historical data are available, the only sensible way to achieve uncertainty quantification is through eliciting ex-15

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“…() on classic techniques, and Sutton and Abrams () and Higgins et al. () on Bayesian methods in the context of meta‐analysis. Statistical methods for integrating different types of studies in order to allow decisions based on all available evidence and to analyse uncertainty (Small, ; Turner et al., ; Gosling et al., ). Quantitative expert judgement including multicriteria decision analysis for integrating different types of studies (Linkov et al., , ). Machine learning techniques (Li and Ngom, ). In silico tools including QSAR, PBTK‐TD (ECHA, ).…”

Section: Overview Of Qualitative and Quantitative Methods For Weight mentioning

confidence: 99%

Guidance on the use of the weight of evidence approach in scientific assessments

Hardy¹,

Benford²,

Halldórsson³

et al. 2017

EFS2

278

216

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EFSA requested the Scientific Committee to develop a guidance document on the use of the weight of evidence approach in scientific assessments for use in all areas under EFSA's remit. The guidance document addresses the use of weight of evidence approaches in scientific assessments using both qualitative and quantitative approaches. Several case studies covering the various areas under EFSA's remit are annexed to the guidance document to illustrate the applicability of the proposed approach. Weight of evidence assessment is defined in this guidance as a process in which evidence is integrated to determine the relative support for possible answers to a question. This document considers the weight of evidence assessment as comprising three basic steps: (1) assembling the evidence into lines of evidence of similar type, (2) weighing the evidence, (3) integrating the evidence. The present document identifies reliability, relevance and consistency as three basic considerations for weighing evidence.

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A Bayes Linear Approach to Weight-of-Evidence Risk Assessment for Skin Allergy

Cited by 18 publications

References 6 publications

Weight of Evidence for Hazard Identification: A Critical Review of the Literature

Weight of Evidence for Hazard Identification: A Critical Review of the Literature

Expert judgement for dependence in probabilistic modelling: A systematic literature review and future research directions

Guidance on the use of the weight of evidence approach in scientific assessments

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