Restricted maximum likelihood estimation of a common mean and the Mandel-Paule algorithm

DOI10.1016/S0378-3758(99)00098-1zbMath0943.62024WikidataQ115926466 ScholiaQ115926466MaRDI QIDQ1970855

Brad J. Biggerstaff, Mark G. Vangel, Andrew. L. Rukhin

Publication date: 10 September 2000

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

zbMATH Keywords

heteroscedasticityvariance componentsgeneralized Bayes estimatorrestricted maximum likelihood estimatorinterlaboratory studyMandel-Paule algorithmunbalanced one-way ANOVA model

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Asymptotic distribution theory in statistics (62E20) Parametric inference under constraints (62F30) Applications of statistics (62P99)

Related Items (10)

Estimating common vector parameters in interlaboratory studies ⋮ Quantifying uncertainty in method of moments estimates of the heterogeneity variance in random effects meta‐analysis ⋮ Noninformative priors for the between-group variance in the unbalanced one-way random effects model with heterogeneous error variances ⋮ Tracking truth through measurement and the spyglass of statistics ⋮ Heterogeneity and study size in random-effects meta-analysis ⋮ Patient-specific meta-analysis for risk assessment using multivariate proportional hazards regression ⋮ Non-informative priors for the common mean in the one-way random effects model with heterogeneous error variances ⋮ Higher order inference for the consensus mean in inter-laboratory studies ⋮ An overdispersion model in meta-analysis ⋮ Robust R-Estimation of a Consensus Value from Multi-Center Studies

Cites Work

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• REML estimation: Asymptotic behavior and related topics
• Estimation of a Common Mean and Weighted Means Statistics
• Estimators for the One-Way Random Effects Model with Unequal Error Variances
• Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
• Consensus Values and Weighting Factors
• REML Estimation of Covariance Matrices with Restricted Parameter Spaces
• Interlaboratory Comparisons: Round Robins with Random Effects
• The Combination of Estimates from Different Experiments

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