A concept of interlaboratory consensus for categorical characteristics of a substance, material, or object

Ilya Kuselman, Consultant, Modiin, Israel (ilya.kuselman@bezeqint.net)
Tamar Gadrich, Braude College Of Engineering, Karmiel, Israel
Francesca R. Pennecchi, Istituto Nazionale Di Ricerca Metrologica , Turin, Italy
D. Brynn Hibbert, School Of Chemistry, University Of New South Wales Sydney, Sydney, Australia
Anastasia A. Semenova, V. M. Gorbatov Federal Research Center For Food Systems, Moscow, Russia

 Interlaboratory studies are widely used for: 1) evaluation of calibration and measurement capabilities of national metrology institutes and designated institutes participating in key and supplementary comparisons; 2) estimation of proficiency (competence) of calibration and testing laboratories; and 3) development of certified reference materials. When a reference value for the measurand is unknown, the laboratory results may be used to estimate (build) a measurand consensus value applicable instead of the reference value. The consensus value typically is: 1) an arithmetic mean of the measured values, when their associated measurement uncertainties are approximately equal; 2) a weighted mean with weights calculated considering the measurement uncertainties; 3) a Bayesian estimator; or another kind of mean.

 However, no algebraic operations and mathematical functions exist among categorical characteristics of a substance, material, or object. Therefore, a consensus numerical value (such as a mean) in an interlaboratory comparison of categorical properties cannot be formulated. In sociology, consensus of opinions within a given group of individuals is discussed as ‘cohesiveness’ or ‘closeness’, i.e., the degree to which the members of the group agree. Consensus of responses of experts of different laboratories participating in an interlaboratory comparison, classifying a substance, material, or object according to its nominal and ordinal characteristics, could also be interpreted as cohesiveness. The recently developed two-way factorial analysis of variation of nominal (categorical) variables CATANOVA and of ordinal variables ORDANOVA, included a detailed decomposition of the total variation, answers the question ‘is a consensus of participating laboratories achieved or not?’ The answer is based on testing hypotheses about homogeneity of the between-laboratory and within-laboratory variation components, as well as the components caused by other factors under study.Enter the body of your abstract here

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Short Biography of Presenting Author

Ilya Kuselman, https://orcid.org/0000-0002-5813-9051, has received his PhD in inorganic chemistry from Kalinin State University, and DSc in analytical chemistry – from R&D Institute for Rare Metal Industry, Moscow, Russia. Since 1971 to 1990 Ilya has been a researcher and then Head of Metrology in Chemistry Division of All-Union R&D Institute of Non-ferrous Secondary Metals, Donetsk, Ukraine, former USSR. Since 1991 to 2014 he was a co-worker and further Director of the National Physical Laboratory of Israel. Now Ilya is Independent Consultant on Metrology. He has published above 200 papers on metrology and quality in analytical chemistry. Ilya is a member of CITAC and ISO/TC 334, IUPAC Analytical Chemistry Division and Subcommittee on Metrology in Chemistry.