Mixture models and disease mapping
P Schlattmann, D Böhning - Statistics in medicine, 1993 - Wiley Online Library
P Schlattmann, D Böhning
Statistics in medicine, 1993•Wiley Online LibraryThe analysis and recognition of disease clustering in space and its representation on a map
is one of the oldest problems in epidemiology. Some traditional methods of constructing
such a map are presented. An alternative approach using mixture models to identify
population heterogeneity and map construction within an empirical Bayes framework is
described. For hepatitis B data from Berlin in 1989, a map is presented and the different
methods are evaluated using a parametric bootstrap approach.
is one of the oldest problems in epidemiology. Some traditional methods of constructing
such a map are presented. An alternative approach using mixture models to identify
population heterogeneity and map construction within an empirical Bayes framework is
described. For hepatitis B data from Berlin in 1989, a map is presented and the different
methods are evaluated using a parametric bootstrap approach.
Abstract
The analysis and recognition of disease clustering in space and its representation on a map is one of the oldest problems in epidemiology. Some traditional methods of constructing such a map are presented. An alternative approach using mixture models to identify population heterogeneity and map construction within an empirical Bayes framework is described. For hepatitis B data from Berlin in 1989, a map is presented and the different methods are evaluated using a parametric bootstrap approach.
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