Abstract
Many collaborative studies are run to evaluate precision of measurement methods. The main focus is on estimating repeatability and reproducibility, which are the variation within a laboratory and the overall variation of the measurement method, respectively. ISO 5725 provides how to design and analyze such precision experiments for quantitative cases where the measurement results follow a continuous distribution, namely a normal distribution. However, there are cases where the measurement results are qualitative such as binary or categorical. In this paper, the cases with ordinal categorical variables are considered. Using methods that can be applied to qualitative data, an analysis of a measurement precision experiment with measurements involving ordinal categorical variables is investigated. The data analysed are from an actual precision experiment of intratracheal administration testing whose objectives were to study the precision of a standardized test method for evaluating nanomaterial pulmonary toxicity.
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References
International Organization for Standardization. (1994). ISO 5725–1 Accuracy (trueness and precision) of measurement methods and results - Part 1: General principles and definitions. Geneva: ISO.
International Organization for Standardization. (1994). ISO 5725–2 Accuracy (trueness and precision) of measurement methods and results - Part 2: Basic method for the determination of repeatability and reproducibility of a standard measurement method. Geneva: ISO.
Wilrich, P-Th. (2010). The determination of precision of qualitative measurement methods by interlaboratory experiments. Accreditation and Quality Assurance, 15(8), 439–444.
de Mast, J., & van Wieringen, W. (2010). Modeling and evaluating repeatability and reproducibility of ordinal classifications. Technometrics, 52(1), 94–106.
Bashkansky, E., Gadrich, T., & Kuselman, I. (2012). Interlaboratory comparison of test results of an ordinal or nominal binary: Analysis of variation. Accreditation and Quality Assurance, 17(3), 239–444.
Muraki, E. (1992). A generalized partial credit model: Application of an EM algorithm. Applied Psychological Measurement, 16(2), 159–176.
The National Institute of Advanced Industrial Science and Technology (AIST), (2018). Annual Report on a Project ‘Survey on standardization of intratracheal administration study for nanomaterials and related issues’. In Japanese, Accessed 2019-05-31: http://www.meti.go.jp/meti_lib/report/H29FY/000102.pdf.
International Organization for Standardization (ISO). (2010). ISO/TR 14468 Selected illustrations of attribute agreement analysis. Geneva: ISO.
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Suzuki, T., Takeshita, Ji., Ogawa, M., Lu, XN., Ojima, Y. (2021). Analysis of Measurement Precision Experiment with Ordinal Categorical Variables. In: Knoth, S., Schmid, W. (eds) Frontiers in Statistical Quality Control 13. ISQC 2019. Frontiers in Statistical Quality Control. Springer, Cham. https://doi.org/10.1007/978-3-030-67856-2_17
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DOI: https://doi.org/10.1007/978-3-030-67856-2_17
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