Statistics Research » Survey Statistics

Small Area Estimation

We leverage advances in statistics and computing power to offer a viable and affordable way to produce valid and reliable estimates for small areas. Our expertise can help state and local agencies design health promotion and prevention activities using sound and robust local, area-specific data pertaining to counties, groups of counties, health service areas, and other administrative units.

We use geographic information system (GIS) software to create graphical applications such as mapping disease incidence or substance use rates. The combined power of our statistical and geographic science expertise provides outstanding value to our clients.

Methodologies/Capabilities

We have developed an innovative survey weighted hierarchical Bayes (SWHB) solution for fitting mixed logistic models. The SWHB method for fitting mixed logistic models offers the following benefits over other hierarchical Bayes solutions:

  • Small area estimates (SAEs) for large sample areas are close to their design-based analogs; hence, they are robust against model mis-specification.
  • Aggregates (national) of lower-level (state, county) estimates are design-consistent and approximately benchmarked to the robust design-based estimates.
  • Person- or unit-level predictors as well as aggregate-level predictors can be used in the model, making SWHB SAEs internally consistent and more precise.

Selected Projects

  • National Survey on Drug Use and Health (NSDUH). The SWHB solution has been implemented on data from the U.S. Substance Abuse and Mental Health Administration's (SAMHSA) National Household Survey on Drug Use and Health (NSDUH) to produce annual state-level and biennial sub-state-level (groups of counties or census tracts) SAEs since 1999 for more than 20 binary outcomes related to substance use, treatment, and mental health. These estimates are being used for treatment planning purposes by the states.
     
  • Diabetes and smoking study. Our statisticians have worked on a research grant awarded to the UNC Center for Health Statistics Research by the Centers for Disease Control and Prevention to produce county-level prevalence estimates of diabetes and smoking for all counties in North Carolina using behavioral risk factor surveillance system (BRFSS) data. These estimates based on the 1996 to 2002 BRFSS data were used to identify high-risk areas (counties or groups of counties) at which prevention and other health intervention programs can be directed.
     
  • Travel study. SAE methodology was used to produce state-level prevalence rates for high daily person miles of travel and associated prediction intervals (PIs) for all 50 states and the District of Columbia, using the 2001 National Household Transportation Survey (NHTS). This project was funded by the Bureau of Transportation Statistics (BTS).