Introduction of Meeting Paper

Society for Risk Analysis-Europe 1997 Annual Meeting

Evaluation of Calibration Variables for Optimising Expert Judgements in Risk Assessments. L. H. J. Goossens and R. M. Cooke, Safety Science Group, Delft University of Technology, Kanaalweg 2 B NL-2628 EB Delft, The Netherlands

Delft University of Technology has under contract to the EC and in cooperation with other EU institutes, completed a study with the United States Nuclear Regulatory Commission (USNRC) using formal expert judgement methods for retrieving uncertainty distributions over the major parameters in the dispersion and deposition module of accident consequence assessment codes (ACA) for nuclear risk assessments. In the study formal expert judgement methods were applied.

In applying these methods, expert assessments need be aggregated to retrieve one combined uncertainty distribution over each assessed variable of interest. In these studies, two methods of combining expert assessments were applied: equal and performance based weighting schemes. The merits and disadvantages of different weighting schemes remain a subject of ongoing scientific discussion and research. Increasingly the merits of performance based weighting are being recognized where appropriate seed variables can be developed for their application.

Seed variables are variables which originate from experimental evidence and of which the true values are unknown to the experts, but are known to the analysts performing the expert judgement studies. The seed variables serve as a basis for calibrating the experts! performance on the variables of interest. In the equal weighting scheme, the experts are assigned equal weights for each assessment. In the performance based weighting scheme experts are weighted according to their performance on the seed variables.

Because the choice of weighting schemes is likely to be subject of continuous discussion and debate and in some cases may become contentious, there was a need in parallel to undertake a more formal analysis of the merits of different schemes so that the optimum choice of weighting scheme can be made in each expert judgement exercise.

 


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