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Guidance on Uncertainty Analysis in Scientific Assessments

Research output: Contribution to Journal/MagazineJournal articlepeer-review

  • Diane Benford
  • Thorhallur Halldorsson
  • Michael John Jeger
  • Helle Katrine Knutsen
  • Simon More
  • Hanspeter Naegeli
  • Hubert Noteborn
  • 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
Article number05123
<mark>Journal publication date</mark>01/2018
<mark>Journal</mark>EFSA Journal
Issue number1
Number of pages39
Publication StatusPublished
Early online date28/01/18
<mark>Original language</mark>English


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.

Bibliographic note

doi: 10.2903/j.efsa.2018.5123