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Estimating common vector parameters in interlaboratory studies

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  • Rukhin, Andrew L.

Abstract

The primary goal of this work is to extend two methods of random effects models to multiparameter situation. These methods comprise the DerSimonian-Laird estimator, stemming from 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.

Suggested Citation

  • Rukhin, Andrew L., 2007. "Estimating common vector parameters in interlaboratory studies," Journal of Multivariate Analysis, Elsevier, vol. 98(3), pages 435-454, March.
    • Handle: RePEc:eee:jmvana:v:98:y:2007:i:3:p:435-454
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    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(06)00140-0
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    References listed on IDEAS

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    1. Mark G. Vangel & Andrew L. Rukhin, 1999. "Maximum Likelihood Analysis for Heteroscedastic One-Way Random Effects ANOVA in Interlaboratory Studies," Biometrics, The International Biometric Society, vol. 55(1), pages 129-136, March.
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    Cited by:

    1. Jian Zhao & Thomas Mathew, 2018. "Some Point Estimates and Confidence Regions for Multivariate Inter-laboratory Data Analysis," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 147-166, December.

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