Bayesian model comparison and model averaging for small-area estimation
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.
Cite
@article{arxiv.0905.3620,
title = {Bayesian model comparison and model averaging for small-area estimation},
author = {Murray Aitkin and Charles C. Liu and Tom Chadwick},
journal= {arXiv preprint arXiv:0905.3620},
year = {2009}
}
Comments
Published 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)