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Int. J. Environ. Res. Public Health 2010, 7(2), 380-394; doi:10.3390/ijerph7020380

On Application of the Empirical Bayes Shrinkage in Epidemiological Settings

1
Institute of Advanced Studies, Charles Darwin University, Darwin NT 0909, Australia
2
Health Gains Planning Branch, Department of Health and Families, NT 0801, Australia
3
School of Public Health, Curtin Health Innovation Research Institute, Curtin University of Technology, WA 6845, Australia
*
Author to whom correspondence should be addressed.
Received: 29 December 2009 / Accepted: 27 December 2010 / Published: 28 January 2010
(This article belongs to the Special Issue Advances in Epidemiology)
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Abstract

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.
Keywords: analysis of variance; computer simulation; reliability and validity; statistical bias; statistical data analysis analysis of variance; computer simulation; reliability and validity; statistical bias; statistical data analysis
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Zhao, Y.; Lee, A.H.; Barnes, T. On Application of the Empirical Bayes Shrinkage in Epidemiological Settings. Int. J. Environ. Res. Public Health 2010, 7, 380-394.

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