Bayesian Interval Estimates of Variance Components Used in Quality Improvement Studies

Article

Lawson, John   (ASQ; Taylor & Francis)   Brigham Young University

Quality Engineering    Vol. 20    No. 3
QICID: 24453    July 2008    pp. 334-345
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Article Abstract

[This abstract is based on the author’s abstract.] Gage R&R studies and nested sampling studies are used in quality assurance and process improvement to estimate variance components. While there are several methods available to analyze data from these studies, interval estimates are not available in the output of commonly used software, and only approximate standard errors of variance components have been proposed for unbalanced nested designs. Bayesian methods provide a solution by guaranteeing nonnegative estimates of variance components and by providing exact interval estimates and functions of individual variance components. Additionally, Bayesian estimates can be computed easily with public domain software.

Keywords

Gage Repeatability and reproducibility studies (GR&R), Nested experiments, Bayesian methods, Variance components, Quality improvement (QI), Quality assurance (QA)


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