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Licence: CC BY-ND: Creative Commons Attribution-NoDerivatives 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Guidance on Uncertainty Analysis in Scientific Assessments. / Benford, Diane; Halldorsson, Thorhallur; Jeger, Michael John et al.
In: EFSA Journal, Vol. 16, No. 1, 05123, 01.2018.Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Guidance on Uncertainty Analysis in Scientific Assessments
AU - Benford, Diane
AU - Halldorsson, Thorhallur
AU - Jeger, Michael John
AU - Knutsen, Helle Katrine
AU - More, Simon
AU - Naegeli, Hanspeter
AU - Noteborn, Hubert
AU - Ockleford, Colin
AU - Ricci, Antonia
AU - Rychen, Guido
AU - Schlatter, Josef R
AU - Silano, Vittorio
AU - Solecki, Roland
AU - Turck, Dominique
AU - Younes, Maged
AU - Craig, Peter
AU - Hart, Andrew
AU - Von Goetz, Natalie
AU - Koutsoumanis, Kostas
AU - Mortensen, Alicja
AU - Ossendorp, Bernadette
AU - Martino, Laura
AU - Merten, Caroline
AU - Mosbach-Schulz, Olaf
AU - Hardy, Anthony
N1 - doi: 10.2903/j.efsa.2018.5123
PY - 2018/1
Y1 - 2018/1
N2 - 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.
AB - 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.
KW - uncertainty analysis
KW - scientific assessment
KW - guidance
U2 - 10.2903/j.efsa.2018.5123
DO - 10.2903/j.efsa.2018.5123
M3 - Journal article
VL - 16
JO - EFSA Journal
JF - EFSA Journal
SN - 1831-4732
IS - 1
M1 - 05123
ER -