title: Models to estimate overall analytical measurements uncertainty: assumptions, comparisons and applications.
abstract: Evaluation of analytical results reliability is of core importance as crucial decisions are taken with them. From the various methodologies to evaluate the fitness of purpose of analytical methods, overall measurement uncertainty estimation is more and more applied. Overall measurement uncertainty allows to combine simultaneously the remaining systematic influences to the random sources of uncertainty and allows assessing the reliability of results generated by analytical methods. However there are various interpretations on how to estimate overall measurement uncertainty, and thus various models for estimating it. Each model together with its assumptions has great impacts on the risks to abusively declare that analytical methods are suitable for their intended purpose. This review paper aims at (i) summarizing the various models used to estimate overall measurement uncertainty, (ii) provide their pros and cons, (iii) review the main areas of application and (iv) as a conclusion provide some recommendations when evaluating overall measurement uncertainty.
authors.affiliation: Analytical Chemistry Laboratory, CIRM, University of Liège, Avenue de l'Hôpital 1, B36, 4000 Liège, Belgium. eric.rozet@ulg.ac.be
authors.forename: E
authors.initials: E
authors.lastname: Rozet
authors.forename: S
authors.initials: S
authors.lastname: Rudaz
authors.forename: R D
authors.initials: RD
authors.lastname: Marini
authors.forename: E
authors.initials: E
authors.lastname: Ziémons
authors.forename: B
authors.initials: B
authors.lastname: Boulanger
authors.forename: Ph
authors.initials: P
authors.lastname: Hubert
mesh_terms: D000818:Animals; D002623:Chemistry Techniques, Analytical / Q000379:methods*; D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D011786:Quality Control; D015203:Reproducibility of Results; D035501:Uncertainty