Some Bayesian and Non-Bayesian Procedures for the Analysis of Comparative Experiments and for Small-Area Estimation: Computational Aspects, Frequentist Properties, and Relationships

Autor:	David A. Harville, Frederick L. Hulting
Rok vydání:	1991
Předmět:	Statistics and Probability Bayesian statistics Small area estimation Frequentist inference Bayesian probability Statistics Prior probability Applied mathematics Statistics Probability and Uncertainty Best linear unbiased prediction Bayesian linear regression Random effects model Mathematics
Zdroj:	Journal of the American Statistical Association. 86:557-568
ISSN:	1537-274X 0162-1459
DOI:	10.1080/01621459.1991.10475080
Popis:	The estimation of a treatment contrast from experimental data and the estimation of a small-area mean are special cases of the prediction of the realization of a linear combination of fixed and random effects in a possibly unbalanced two-part mixed linear model. In this article a Bayesian approach to point and interval prediction is presented and its computational requirements are examined. Differences between the Bayesian approach and the traditional (classical) approach are discussed in general terms and, in addition, in terms of two examples taken from the literature: (1) the comparison of drug formulations in a bioavailability trial (Westlake) and (2) the estimation of corn-crop areas using satellite data (Battese, Harter, and Fuller). Some deficiencies in the classical approach are pointed out, and the Bayesian approach is considered from a frequentist perspective. It is shown, via a Monte Carlo study, that, for certain (noninformative) choices of the prior distribution, the frequentist prop...
Databáze:	OpenAIRE
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