The Annals of Applied Statistics

Bayesian model comparison and model averaging for small-area estimation

Murray Aitkin, Charles C. Liu, and Tom Chadwick

Full-text: Open access

Abstract

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.

Article information

Source
Ann. Appl. Stat. Volume 3, Number 1 (2009), 199-221.

Dates
First available in Project Euclid: 16 April 2009

Permanent link to this document
http://projecteuclid.org/euclid.aoas/1239888368

Digital Object Identifier
doi:10.1214/08-AOAS205

Zentralblatt MATH identifier
1160.62021

Mathematical Reviews number (MathSciNet)
MR2668705

Citation

Aitkin, Murray; Liu, Charles C.; Chadwick, Tom. Bayesian model comparison and model averaging for small-area estimation. Ann. Appl. Stat. 3 (2009), no. 1, 199--221. doi:10.1214/08-AOAS205. http://projecteuclid.org/euclid.aoas/1239888368.


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