https://www.mdu.se/

mdu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Assessing laboratory effects in key comparisons with two transfer standards measured in two petals: A Bayesian approach
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. Unit of Statistics, School of Business, Örebro University, Sweden. (MAM)
Physikalisch-Technische Bundesanstalt, Berlin, Germany.
2020 (English)In: 13th International Workshop on Intelligent Statistical Quality Control 2019, IWISQC 2019 - Proceedings, City University of Hong Kong , 2020, p. 1-18Conference paper, Published paper (Refereed)
Abstract [en]

We propose a new statistical method for analyzing data from a key comparison when two transfer standards are measured in two petals. The approach is based on a generalization of the classical random effects model, a popular procedure in metrology. A Bayesian treatment of the model parameters as well as of the random effects is suggested. The latter can be viewed as potential laboratory effects which are assessed through the proposed analysis. While the prior for the laboratory effects naturally is assigned as a Gaussian distribution, the Berger & Bernardo reference prior is taken for the remaining model parameters. The results are presented in terms of the posterior distributions derived for the laboratory effects. From these distributions posterior means and credible intervals are calculated. The proposed method paves the way for applying the established random effects model also for data arising from the measurement of several transfer standards in several petals, and it is illustrated for measurements of two 500mg transfer standards carried out in key comparison CCM.M-K7.

Place, publisher, year, edition, pages
City University of Hong Kong , 2020. p. 1-18
Keywords [en]
Bayesian networks, Laboratories, Random processes, Bayesian approaches, Credible interval, Measurements of, Model parameters, Posterior distributions, Random effects model, Reference prior, Transfer standard, Quality control
National Category
Other Engineering and Technologies
Identifiers
URN: urn:nbn:se:mdh:diva-49119Scopus ID: 2-s2.0-85086433741OAI: oai:DiVA.org:mdh-49119DiVA, id: diva2:1447298
Conference
13th International Workshop on Intelligent Statistical Quality Control 2019, IWISQC 2019, 12 August 2019 through 14 August 2019
Available from: 2020-06-25 Created: 2020-06-25 Last updated: 2020-11-02Bibliographically approved

Open Access in DiVA

No full text in DiVA

Scopus

Authority records

Bodnar, Olha

Search in DiVA

By author/editor
Bodnar, Olha
By organisation
Educational Sciences and Mathematics
Other Engineering and Technologies

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 77 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf