Small Area Estimation Methods for Binary Variables in the Behavioral Risk Factor Surveillance System

• Activity Number: 571
• Type: Contributed
• Date/Time: Wednesday, August 6, 2014 : 2:00 PM to 3:50 PM
• Sponsor: Survey Research Methods Section
• Author(s): Neung Ha*+
• Companies: SAMSI
• Keywords: Hierarchical Bayesian modeling ; Small area estimation ; ehavioral Risk Factor Surveillance System ; Generalized mixed effect model ; Bayesian model analysis

Abstract

Large government administered surveys are designed to provide reliable estimates of finite population characteristics for large geographical regions such as the entire U.S. or each of the 50 states, but not for subpopulations and small geographical regions. Our investigation uses the 2010 Behavioral Risk Factor Surveillance System, BRFSS, to make inference at the county level for various population characteristics, such as totals, proportions, or quantiles, for health characteristics like the health insurance rate or the obesity rate.

Our objective, using an example from the BRFSS, is to show how one may routinely develop models and check model fit, leading to accurate Bayesian predictions of finite population quantities for small geographical areas and subpopulations. We check whether there is a selection bias, investigating, in particular, the possible role of conventional survey weights in correcting for selection bias and in improving inferences. We display our results in choropleth maps, together with measures of variation.