When components of a substance or material are subject to a mass balance constraint, test results of the components’ contents are intrinsically correlated because of the constraint. This so-called ‘spurious’ correlation is observed in addition to possible metrologically-related correlation of test results, and natural and/or technological correlation of the components’ contents. Such correlations may influence understanding of test results and evaluation of risks of false decisions, due to measurement uncertainty, in conformity assessment of the substance or material. The objective of the present paper is the development of a technique for appropriate evaluation of the risks. A Bayesian multivariate approach to evaluate the conformance probability of materials or objects and relevant risks is discussed for different scenarios of the data modelling, taking into account all observed correlations. A Monte Carlo method, including the mass balance constraint, written in the R programming environment, is provided for the necessary calculations.

Correlation of test results and influence of a mass balance constraint on risks in conformity assessment of a substance or material / Pennecchi, Francesca R.; Di Rocco, Aglaia; Kuselman, Ilya; Hibbert, D. Brynn; Sega, Michela. - In: MEASUREMENT. - ISSN 0263-2241. - 163:(2020), p. 107947. [10.1016/j.measurement.2020.107947]

Correlation of test results and influence of a mass balance constraint on risks in conformity assessment of a substance or material

Pennecchi, Francesca R.;Sega, Michela
2020

Abstract

When components of a substance or material are subject to a mass balance constraint, test results of the components’ contents are intrinsically correlated because of the constraint. This so-called ‘spurious’ correlation is observed in addition to possible metrologically-related correlation of test results, and natural and/or technological correlation of the components’ contents. Such correlations may influence understanding of test results and evaluation of risks of false decisions, due to measurement uncertainty, in conformity assessment of the substance or material. The objective of the present paper is the development of a technique for appropriate evaluation of the risks. A Bayesian multivariate approach to evaluate the conformance probability of materials or objects and relevant risks is discussed for different scenarios of the data modelling, taking into account all observed correlations. A Monte Carlo method, including the mass balance constraint, written in the R programming environment, is provided for the necessary calculations.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11696/66176
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