 Mapping Disease and Mortality Rates Using Empirical Bayes EstimatorsRoger J. Marshall Journal of the Royal Statistical Society Series C, 1991, vol. 40, issue 2, 283-294 Abstract: Methods for estimating regional mortality and disease rates, with a view to mapping disease, are discussed. A new empirical Bayes estimator, with parameters simply estimated by moments, is proposed and compared with iterative alternatives suggested by Clayton and Kaldor. These methods are shrinkage estimators, in which the crude disease rate is shrunk towards an overall regional rate, and are in this sense ‘global’ and invariant to spatial configuration. However, it seems unjustifiable, in effect, to ignore the spatial aspect of the problem. A ‘local’ shrinkage estimator is therefore also suggested in which the crude rate is shrunk towards a local, neighbourhood, rate. Comparison of the estimators is done by some simulation experiments and an example showing infant mortality in Auckland, New Zealand, is presented. When disease is relatively rare a global estimator gives the lowest total mean‐square error, but for diseases that are more common and where the underlying spatial pattern is not uniform the local estimator performs best. Date: 1991 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:40:y:1991:i:2:p:283-294 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC. |
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