Analysis of measurement precision experiment with categorical variables

Tomomichi Suzuki, Jun Ichi Takeshita, Mayu Ogawa, Xiao-Nan Lu, Yoshikazu Ojima

Research output: Contribution to conferencePaper

Abstract

Evaluating performance of a measurement method is essential in metrology. Concepts of repeatability and reproducibility are introduced in ISO5725-1 (1994) including how to run and analyse experiments (usually collaborative studies) to obtain these precision measures. ISO5725-2 (1994) describe precision evaluation in quantitative measurements but not in qualitative measurements. Some methods have been proposed for qualitative measurements cases such as Wilrich (2010), de Mast & van Wieringen (2010), Bashkansky, Gadrich & Kuselman (2012). Item response theory (Muraki, 1992) is another methodology that can be used to analyse qualitative data. Utilizing these methods, analysis of measurement precision experiment is investigated when the measurements involve categorical variables. The data analysed are from the precision experiment of intratracheal administration testing (AIST, 2018) whose objectives were to study the precision of the standardized test method for evaluating the pulmonary toxicity of nanomaterials. In such experiments, dose-response relationship also need to be considered which makes the situation more complicated. We discuss how these data should be analysed using actual data.

Original languageEnglish
Pages249-260
Number of pages12
Publication statusPublished - 1 Jan 2020
Event13th International Workshop on Intelligent Statistical Quality Control 2019, IWISQC 2019 - Hong Kong, Hong Kong
Duration: 12 Aug 201914 Aug 2019

Conference

Conference13th International Workshop on Intelligent Statistical Quality Control 2019, IWISQC 2019
CountryHong Kong
CityHong Kong
Period12/08/1914/08/19

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    Suzuki, T., Takeshita, J. I., Ogawa, M., Lu, X-N., & Ojima, Y. (2020). Analysis of measurement precision experiment with categorical variables. 249-260. Paper presented at 13th International Workshop on Intelligent Statistical Quality Control 2019, IWISQC 2019, Hong Kong, Hong Kong.