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dc.contributor.authorHewson, P.J.en_GB
dc.contributor.authorBailey, Trevor C.en_GB
dc.date.accessioned2013-03-11T15:56:59Zen_GB
dc.date.accessioned2013-03-20T12:24:48Z
dc.date.issued2010-09-28en_GB
dc.description.abstractThere has been considerable recent interest in multivariate modelling of the geographical distribution of morbidity or mortality rates for potentially related diseases. The motivations for this include investigation of similarities or dissimilarities in the risk distribution for the different diseases, as well as ‘borrowing strength’ across disease rates to shrink the uncertainty in geographical risk assessment for any particular disease. A number of approaches to such multivariate modelling have been suggested and this paper proposes an extension to these which may provide a richer range of dependency structures than those encompassed so far. We develop a model which incorporates a discrete mixture of latent structures and argue that this provides potential to represent an enhanced range of correlation structures between diseases at the same time as implicitly allowing for less restrictive spatial correlation structures between geographical units. We compare and contrast our approach to other commonly used multivariate disease models and demonstrate comparative results using data taken from cancer registries on four carcinomas in some 300 geographical units in England, Scotland and Wales.en_GB
dc.identifier.citationVol. 10 (3), pp. 241 - 264en_GB
dc.identifier.doi10.1177/1471082X0801000301en_GB
dc.identifier.urihttp://hdl.handle.net/10036/4453en_GB
dc.language.isoenen_GB
dc.publisherSAGE Publicationsen_GB
dc.subjectfactor analysisen_GB
dc.subjectlatent structureen_GB
dc.subjectmixture modelen_GB
dc.subjectmultivariate disease ratesen_GB
dc.titleModelling multivariate disease rates with a latent structure mixture modelen_GB
dc.typeArticleen_GB
dc.date.available2013-03-11T15:56:59Zen_GB
dc.date.available2013-03-20T12:24:48Z
dc.identifier.issn1471-082Xen_GB
dc.descriptionCopyright © 2013 SAGE / Statistical Modeling Societyen_GB
dc.identifier.eissn1477-0342en_GB
dc.identifier.journalStatistical Modellingen_GB


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