DEPARTMENT OF STATISTICS
Statistics Colloquium
University of Connecticut
Storrs, Connecticut
The Department of Statistics Cordially invites you to a Colloquium
Cici Bauer
Department of Biostatistics
Brown University
Bayesian spatial models for small area estimation with
complex survey data
ABSTRACT
Small area estimation (SAE) is an important endeavor since many agencies require estimates of health, education and environmental measures in order to plan and allocate resources and target interventions. The data upon which SAE is based are often gathered via complex designs, and it is important to take into account of such design when modeling the data. We develop computationally efficient Bayesian spatial smoothing models that acknowledge the complex survey design. An extensive simulation study is presented that considers the effects of non-response and non-random selection of individuals, allowing examination of the impact of ignoring the design weights and the benefits of spatial smoothing. The results show that, when compared with standard approaches, mean squared error can be greatly reduced with the proposed methods. Bias reduction occurs through the inclusion of the design weights, with variance reduction being achieved through spatial smoothing. The application of our proposed approach is illustrated with data from the Washington State 2006 Behavioral Risk Factor Surveillance System. The models are easily and quickly fitted within the R environment, using existing packages.
DATE: Wednesday, November 5, 2014
TIME: 4:00 p.m.
PLACE: Philip E. Austin Building – Room 105
Coffee will be served at 3:30 in room 326
For more information, contact: Tracy Burke at tracy.burke@uconn.edu