EFSA Journal (Jan 2018)

Guidance on Uncertainty Analysis in Scientific Assessments

  • EFSA Scientific Committee,
  • Diane Benford,
  • Thorhallur Halldorsson,
  • Michael John Jeger,
  • Helle Katrine Knutsen,
  • Simon More,
  • Hanspeter Naegeli,
  • Hubert Noteborn,
  • Colin Ockleford,
  • Antonia Ricci,
  • Guido Rychen,
  • Josef R Schlatter,
  • Vittorio Silano,
  • Roland Solecki,
  • Dominique Turck,
  • Maged Younes,
  • Peter Craig,
  • Andrew Hart,
  • Natalie Von Goetz,
  • Kostas Koutsoumanis,
  • Alicja Mortensen,
  • Bernadette Ossendorp,
  • Laura Martino,
  • Caroline Merten,
  • Olaf Mosbach‐Schulz,
  • Anthony Hardy

DOI
https://doi.org/10.2903/j.efsa.2018.5123
Journal volume & issue
Vol. 16, no. 1
pp. n/a – n/a

Abstract

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Abstract Uncertainty analysis is the process of identifying limitations in scientific knowledge and evaluating their implications for scientific conclusions. It is therefore relevant in all EFSA's scientific assessments and also necessary, to ensure that the assessment conclusions provide reliable information for decision‐making. The form and extent of uncertainty analysis, and how the conclusions should be reported, vary widely depending on the nature and context of each assessment and the degree of uncertainty that is present. This document provides concise guidance on how to identify which options for uncertainty analysis are appropriate in each assessment, and how to apply them. It is accompanied by a separate, supporting opinion that explains the key concepts and principles behind this Guidance, and describes the methods in more detail.

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