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Estimating Common Vector Parameters in Interlaboratory Studies

Published

Author(s)

Andrew L. Rukhin

Abstract

The primary goal of this work is to extend two methodsof random effects models to multiparameter situation. These methods comprise the DerSimonian-Laird estimator, arising in the meta-analysis, and the Mandel-Paule algorithm widely used in interlaboratory studies. The maximum likelihood estimators are also discussed. Two methods of assessing the uncertainty of these estimators are given, and a study of the theoretical properties of these methods is performed.
Citation
Journal of Multivariate Analysis
Volume
98
Issue
3

Keywords

Consensus mean, General linear model, DerSimonian-Laird estimator, Interlaboratory study, Mandel-Paule algorithm, Meta-analysis, Random effects model

Citation

Rukhin, A. (2007), Estimating Common Vector Parameters in Interlaboratory Studies, Journal of Multivariate Analysis, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=150395 (Accessed June 13, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created March 13, 2007, Updated February 19, 2017