On Application of the Empirical Bayes Shrinkage in Epidemiological Settings

Bibliographic Data

ID15500562
AuthorsYuejen Zhao (0000-0002-5775-4503, Charles Darwin University, corresponding author), Andy H Lee (0000-0003-4120-5005, Curtin University), Tony Barnes (Charles Darwin University)
Year2010
Volume7
Issue2
Pages380-394
Publication date2010-01-28
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph7020380
PMID20616980
PMCIDPMC2872278
OpenAlexW2013290380
LanguageEN
References cited29

This paper aims to provide direct and indirect evidence on setting up rules for applications of the empirical Bayes shrinkage (EBS), and offers cautionary remarks concerning its applicability. In epidemiology, there is still a lack of relevant criteria in the application of EBS. The bias of the shrinkage estimator is investigated in terms of the sums of errors, squared errors and absolute errors, for both total and individual groups. The study reveals that assessing the underlying exchangeability assumption is important for appropriate use of EBS. The performance of EBS is indicated by a ratio statistic f of the between-group and within-group mean variances. If there are significant differences between the sample means, EBS is likely to produce erratic and even misleading information

Bayes factor · Bayes' theorem · Bayesian probability · Bias of an estimator · Econometrics · Estimator · Minimum-variance unbiased estimator · Shrinkage · Shrinkage estimator · Statistic · Statistics · Computer Science · Genetic and phenotypic traits in livestock · Genetics and Plant Breeding · Mathematics · Statistical Methods and Bayesian Inference

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