Bias in analytical chemistry: A review of selected procedures for incorporating uncorrected bias into the expanded uncertainty of analytical measurements and a graphical method for evaluating the concordance of reference and test procedures

Frenkel, R, Farrance, I and Badrick, T 2019, 'Bias in analytical chemistry: A review of selected procedures for incorporating uncorrected bias into the expanded uncertainty of analytical measurements and a graphical method for evaluating the concordance of reference and test procedures', Clinica Chimica Acta, pp. 1-1.


Document type: Journal Article
Collection: Journal Articles

Title Bias in analytical chemistry: A review of selected procedures for incorporating uncorrected bias into the expanded uncertainty of analytical measurements and a graphical method for evaluating the concordance of reference and test procedures
Author(s) Frenkel, R
Farrance, I
Badrick, T
Year 2019
Journal name Clinica Chimica Acta
Start page 1
End page 1
Total pages 1
Publisher Elsevier BV
Abstract The Evaluation of measurement data - Guide to the Expression of Uncertainty in Measurement (GUM) provides the framework for evaluating measurement uncertainty. The preferred GUM approach for addressing bias assumes that all systematic errors are identified and corrected at an early stage in the measurement process. We review some procedures for treating uncorrected bias and its inclusion into an overall uncertainty statement. When bias and its uncertainty are recognised as metrological states independent of scatter in the test results, the uncertainty of the reference and uncertainty of the bias can be equated. The net standard uncertainty of a test result is the root-sum-square of the standard uncertainty of the bias and the standard uncertainty of measurements on the test. Since an incomplete and therefore potentially erroneous formula is often used for estimating bias standard uncertainty, we propose an alternative calculation. We next propose a graphical method using a simple algorithm that quantifies the discrepancy between the results of a test measurement and the corresponding reference value, in terms of the percentage overlap of two probability density functions. We propose that bias should be corrected wherever possible and we illustrate this approach using the graphical method. Even though this review is focused principally on analytical chemistry and medical laboratory applications, much of the discussion is applicable to all areas of metrology.
Subject Analytical Chemistry not elsewhere classified
Keyword(s) Measurement uncertainty
Bias
Bias uncertainty
Bias correction
Probability density function
Overlap
DOI - identifier 10.1016/j.cca.2019.03.1633
Copyright notice © 2019 Elsevier BV
ISSN 0009-8981
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