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Analysis of signal–response systems using generalized linear mixed models
Author(s) -
Gupta Shilpa,
Kulahci Murat,
Montgomery Douglas C.,
Borror Connie M.
Publication year - 2010
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.1068
Subject(s) - generalized linear mixed model , variance (accounting) , generalized linear model , mathematics , linear model , mixed model , signal (programming language) , sigma , confidence interval , statistics , computer science , algorithm , accounting , business , programming language , physics , quantum mechanics
Robust parameter design is one of the important tools used in Design for Six Sigma. In this article, we present an application of the generalized linear mixed model (GLMM) approach to robust design and analysis of signal–response systems. We propose a split‐plot approach to the signal–response system characterized by two variance components—within‐profile variance and between‐profile variance. We demonstrate that explicit modeling of variance components using GLMMs leads to more precise point estimates of important model coefficients with shorter confidence intervals. Copyright © 2009 John Wiley & Sons, Ltd.