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Estimating expected value of information using Bayesian belief networks: a case study in fish consumption advisory

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Abstract

A recent international collaborative effort was directed at quantifying the risks and benefits of fish consumption. A nonparametric continuous–discrete Bayesian belief network was constructed to support these calculations. The same Bayesian belief network has enabled calculation of the expected benefits of further research directed at shrinking the uncertainties and prioritization of possible research efforts.

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Notes

  1. For convenience, we will refer to nodes and variables interchangeably.

  2. The bivariate normal copula is the copula of the bivariate normal distribution with the parameter being the Pearson’s product moment correlation.

  3. Birth data for 2007 were chosen for consistency with data on fish consumption. According to Statistics Finland’s population statistics, the number of children born in Finland in 2007 was 58,729 (Official Statistics of Finland 2012).

  4. Note that, both these variables have also been identified as potentially influential to decision making through the sensitivity analysis as discussed before.

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Acknowledgements

The authors wish to thank Mr. Olli Leino, Dr. Jouni T. Tuomisto, Dr. Anna K. Karjalainen and other participants in BENERIS project for guidance and providing data required to quantify the BBN model used in this study.

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Authors and Affiliations

  1. Department of Applied Mathematics, Delft University of Technology, Mekelweg 4, 2628 CD, Delft, The Netherlands

    Patrycja L. Gradowska

  2. Resources for the Future, Washington, DC, USA

    Roger M. Cooke

  3. University of Strathclyde, Glasgow, UK

    Roger M. Cooke

  4. Delft University of Technology, Delft, The Netherlands

    Roger M. Cooke

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  1. Patrycja L. Gradowska
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Correspondence to Patrycja L. Gradowska.

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Gradowska, P.L., Cooke, R.M. Estimating expected value of information using Bayesian belief networks: a case study in fish consumption advisory. Environ Syst Decis 34, 88–97 (2014). https://doi.org/10.1007/s10669-013-9471-4

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