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Metrology of human-based and other qualitative measurements
RISE, SP – Sveriges Tekniska Forskningsinstitut.
2016 (English)In: Measurement science and technology, ISSN 0957-0233, E-ISSN 1361-6501, Vol. 27, no 9, 094003Article in journal (Refereed) Published
Abstract [en]

The metrology of human-based and other qualitative measurements is in its infancy - concepts such as traceability and uncertainty are as yet poorly developed. This paper reviews how a measurement system analysis approach, particularly invoking as performance metric the ability of a probe (such as a human being) acting as a measurement instrument to make a successful decision, can enable a more general metrological treatment of qualitative observations. Measures based on human observations are typically qualitative, not only in sectors, such as health care, services and safety, where the human factor is obvious, but also in customer perception of traditional products of all kinds. A principal challenge is that the usual tools of statistics normally employed for expressing measurement accuracy and uncertainty will probably not work reliably if relations between distances on different portions of scales are not fully known, as is typical of ordinal or other qualitative measurements. A key enabling insight is to connect the treatment of decision risks associated with measurement uncertainty to generalized linear modelling (GLM). Handling qualitative observations in this way unites information theory, the perceptive identification and choice paradigms of psychophysics. The Rasch invariant measure psychometric GLM approach in particular enables a proper treatment of ordinal data; a clear separation of probe and item attribute estimates; simple expressions for instrument sensitivity; etc. Examples include two aspects of the care of breast cancer patients, from diagnosis to rehabilitation. The Rasch approach leads in turn to opportunities of establishing metrological references for quality assurance of qualitative measurements. In psychometrics, one could imagine a certified reference for knowledge challenge, for example, a particular concept in understanding physics or for product quality of a certain health care service. Multivariate methods, such as Principal Component Regression, can also be improved by exploiting the increased resolution of the Rasch approach. © 2016 IOP Publishing Ltd.

Place, publisher, year, edition, pages
2016. Vol. 27, no 9, 094003
Keyword [en]
decision risks, metrology, qualitative, Rasch, uncertainty, Diagnosis, Health care, Information theory, Measurements, Patient rehabilitation, Patient treatment, Principal component analysis, Probes, Quality assurance, Risk assessment, Safety factor, Units of measurement, Measurement instruments, Measurement system analysis, Principal component regression, Qualitative measurements, Qualitative observations, Uncertainty analysis
National Category
Medical Laboratory and Measurements Technologies
Identifiers
URN: urn:nbn:se:ri:diva-27637DOI: 10.1088/0957-0233/27/9/094003Scopus ID: 2-s2.0-84985914689OAI: oai:DiVA.org:ri-27637DiVA: diva2:1059544
Available from: 2016-12-22 Created: 2016-12-21 Last updated: 2017-02-19Bibliographically approved

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CiteExportLink to record
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Citation style
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