Confidence intervals for the comparison of variability estimates for a mixed model

Lorraine Daniels, Connie M. Borror, Richard K. Burdick

Research output: Contribution to journalArticle

Abstract

In this paper, we develop methods for generating confidence intervals for the comparison of variability estimates in a mixed-effects model. A generalized confidence interval (GCI) is developed and contrasted to the modified large sample (MLS) method with an adjustment for a fixed effect. The methods are assessed using a computer simulation. Recommendations are provided for selecting an appropriate method.

Original languageEnglish (US)
Pages (from-to)37-53
Number of pages17
JournalQuality and Reliability Engineering International
Volume24
Issue number1
DOIs
StatePublished - Feb 1 2008

Keywords

  • Analysis of variance
  • Mixed model
  • Variance components

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Management Science and Operations Research

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