Bayesian model comparison and model averaging for small-area estimation

dc.creatorAitkin, Murray
dc.creatorLiu, Charles C.
dc.creatorChadwick, Tom
dc.date2009-05-22
dc.date.accessioned2026-07-07T13:17:33Z
dc.date.available2026-07-07T13:17:33Z
dc.descriptionThis paper considers small-area estimation with lung cancer mortality data, and discusses the choice of upper-level model for the variation over areas. Inference about the random effects for the areas may depend strongly on the choice of this model, but this choice is not a straightforward matter. We give a general methodology for both evaluating the data evidence for different models and averaging over plausible models to give robust area effect distributions. We reanalyze the data of Tsutakawa [Biometrics 41 (1985) 69--79] on lung cancer mortality rates in Missouri cities, and show the differences in conclusions about the city rates from this methodology.
dc.descriptionPublished in at http://dx.doi.org/10.1214/08-AOAS205 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0905.3620
dc.identifierhttp://arxiv.org/abs/0905.3620
dc.identifierAnnals of Applied Statistics 2009, Vol. 3, No. 1, 199-221
dc.identifierdoi:10.1214/08-AOAS205
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/231144
dc.subjectApplications
dc.titleBayesian model comparison and model averaging for small-area estimation
dc.typetext

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