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

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

doi:10.1002/qre.865

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

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

Mathematical and Natural Sciences, School of (SMNS)

Research output: Contribution to journal › Article › peer-review

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 language	English (US)
Pages (from-to)	37-53
Number of pages	17
Journal	Quality and Reliability Engineering International
Volume	24
Issue number	1
DOIs	https://doi.org/10.1002/qre.865
State	Published - Feb 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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10.1002/qre.865

Cite this

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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.",

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

Abstract

Keywords

ASJC Scopus subject areas

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