Adriaan M. H. van der Veen, Maurice G. Cox, Antonio Possolo
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In this paper, we show how the new document takes the reader from the specification of the measurand through the steps needed to arrive at a complete measurement model, suitable for providing a value for the measurand and an associated uncertainty. An important intermediate stage in this process is the description of the measurement principle, as for many users of standardized test methods this principle is already described by a model. This “basic model” needs extension to include effects arising from the measurement, such as calibration, corrections to be applied, repeatability and reproducibility. The document also introduces statistical models, which recognise the dispersion of replicated observations of the same quantity while capturing the fact that all are informative about the true value of the measurand. JCGM GUM-6 is a valuable contribution to the GUM suite in that it provides a structured and flexible approach to the creation, validation, and use of measurement models.</p></div>","PeriodicalId":454,"journal":{"name":"Accreditation and Quality Assurance","volume":"27 5","pages":"295 - 297"},"PeriodicalIF":0.8000,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s00769-022-01509-8.pdf","citationCount":"2","resultStr":"{\"title\":\"GUM guidance on developing and using measurement models\",\"authors\":\"Adriaan M. H. van der Veen, Maurice G. 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In this paper, we show how the new document takes the reader from the specification of the measurand through the steps needed to arrive at a complete measurement model, suitable for providing a value for the measurand and an associated uncertainty. An important intermediate stage in this process is the description of the measurement principle, as for many users of standardized test methods this principle is already described by a model. This “basic model” needs extension to include effects arising from the measurement, such as calibration, corrections to be applied, repeatability and reproducibility. The document also introduces statistical models, which recognise the dispersion of replicated observations of the same quantity while capturing the fact that all are informative about the true value of the measurand. JCGM GUM-6 is a valuable contribution to the GUM suite in that it provides a structured and flexible approach to the creation, validation, and use of measurement models.</p></div>\",\"PeriodicalId\":454,\"journal\":{\"name\":\"Accreditation and Quality Assurance\",\"volume\":\"27 5\",\"pages\":\"295 - 297\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2022-07-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s00769-022-01509-8.pdf\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accreditation and Quality Assurance\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s00769-022-01509-8\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accreditation and Quality Assurance","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s00769-022-01509-8","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
GUM guidance on developing and using measurement models
The GUM suite of documents (Guide to the expression of uncertainty in measurement and related documents) has been expanded with the addition of a new guidance document describing the development and use of measurement models for obtaining a value for the measurand and an associated measurement uncertainty. The methods for estimating the measurand and evaluating measurement uncertainty in the GUM suite all hinge upon a measurement model that relates the measurand to a set of input quantities. Many users find the development of these models challenging, and so far little guidance has been made available for how to address this pervasive challenge. In this paper, we show how the new document takes the reader from the specification of the measurand through the steps needed to arrive at a complete measurement model, suitable for providing a value for the measurand and an associated uncertainty. An important intermediate stage in this process is the description of the measurement principle, as for many users of standardized test methods this principle is already described by a model. This “basic model” needs extension to include effects arising from the measurement, such as calibration, corrections to be applied, repeatability and reproducibility. The document also introduces statistical models, which recognise the dispersion of replicated observations of the same quantity while capturing the fact that all are informative about the true value of the measurand. JCGM GUM-6 is a valuable contribution to the GUM suite in that it provides a structured and flexible approach to the creation, validation, and use of measurement models.
期刊介绍:
Accreditation and Quality Assurance has established itself as the leading information and discussion forum for all aspects relevant to quality, transparency and reliability of measurement results in chemical and biological sciences. The journal serves the information needs of researchers, practitioners and decision makers dealing with quality assurance and quality management, including the development and application of metrological principles and concepts such as traceability or measurement uncertainty in the following fields: environment, nutrition, consumer protection, geology, metallurgy, pharmacy, forensics, clinical chemistry and laboratory medicine, and microbiology.