  In public health management there is a need to produce subnational estimates
of health outcomes. Often, however, funds are not available to collect samples
large enough to produce traditional survey sample estimates for each
subnational area. Although parametric hierarchical methods have been
successfully used to derive estimates from small samples, there is a concern
that the geographic diversity of the U.S. population may be oversimplified in
these models. In this paper, a semi-parametric model is used to describe the
geographic variability component of the model. Specifically, we assume
Dirichlet process mixtures of normals for county-specific random effects.
Results are compared to a parametric model based on the base measure of the
Dirichlet process, using binary health outcomes related to mammogram usage.
