Confidence intervals for variance components in gauge capability studies

Dário Ferreira, Sandra S. Ferreira, Célia Nunes, Teresa A. Oliveira, João T. Mexia

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present a method, that uses pivot variables, which are functions of statistics and parameters, of constructing confidence intervals for variance components in gauge capability studies. As illustration we will consider a study on repeatability and reproducibility measures. Besides this the paper includes a simulation study demonstrating that in approximately 9500 out of 10000 simulations the 95% confidence interval covers the true value of the parameter.

Original languageEnglish
Title of host publicationInternational Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2017
EditorsTheodore Simos, Charalambos Tsitouras
PublisherAmerican Institute of Physics (AIP)
Volume1978
ISBN (Electronic)9780735416901
DOIs
Publication statusPublished - 10 Jul 2018
EventInternational Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2017 - Thessaloniki, Greece
Duration: 25 Sept 201730 Sept 2017

Publication series

NameAIP Conference Proceedings
PublisherAmerican Institute of Physics Inc.
Volume1978
ISSN (Print)0094-243X

Conference

ConferenceInternational Conference of Numerical Analysis and Applied Mathematics, ICNAAM 2017
Country/TerritoryGreece
CityThessaloniki
Period25/09/1730/09/17

Keywords

  • induced probability measures
  • Inference, linear models, variance components, RandR measures

Fingerprint

Dive into the research topics of 'Confidence intervals for variance components in gauge capability studies'. Together they form a unique fingerprint.

Cite this