Bayesian Model Comparison and Model Averaging for Small-Area Estimation

This 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. W...

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Bibliographic Details
Published in:The annals of applied statistics 2009-03, Vol.3 (1), p.199-221
Main Authors: Aitkin, Murray, Liu, Charles C., Chadwick, Tom
Format: Article
Language:English
Subjects:
Bayesian networks
Frequentism
Inference
Lung neoplasms
Modeling
Mortality
Multilevel models
Parametric models
Probabilities
Statistical variance
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Summary:This 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.
ISSN:1932-6157
DOI:10.1214/09-AOAS205