Hierarchical Bayes small area estimation for county-level health prevalence to having a personal doctor

Details

• Alternative Title:
  Stat Methods Appt
• Personal Author:
  Andreea L., Erciulescu ; Jianzhu, Li ; Tom, Krenzke ; Machell, Town
• Description:
  The complexity of survey data and the availability of data from auxiliary sources motivate researchers to explore estimation methods that extend beyond traditional survey-based estimation. The U.S. Centers for Disease Control and Prevention's Behavioral Risk Factor Surveillance System (BRFSS) collects a wide range of health information, including whether respondents have a personal doctor. While the BRFSS focuses on state-level estimation, there is demand for county-level estimation of health indicators using BRFSS data. A hierarchical Bayes small area estimation model is developed to combine county-level BRFSS survey data with county-level data from auxiliary sources, while accounting for various sources of error and nested geographical levels. To mitigate extreme proportions and unstable survey variances, a transformation is applied to the survey data. Model-based county-level predictions are constructed for prevalence of having a personal doctor for all the counties in the U.S., including those where BRFSS survey data were not available. An evaluation study using only the counties with large BRFSS sample sizes to fit the model versus using all the counties with BRFSS data to fit the model is also presented.
• Keywords:
  Behavioral Risk Factor Surveillance System Disaggregation Hierarchical Bayes Multiple Data Sources Nested Levels
• Source:
  Stat Methods Appt. 33:1171-1191
• Pubmed ID:
  39664166
• Pubmed Central ID:
  PMC11633323
• Document Type:
  Journal Article
• Funding:
  CC999999/ImCDC/Intramural CDC HHSUnited States/ ; HHSD2002013M53968B/CC/CDC HHSUnited States/
• Volume:
  33
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha-512:809c2e5171440125455d6dd7ac1e715d94e9beb9a0da66a02ad157440848a2cf06e260d880552e5d5559476284504128812277b3d38749c4c79fcb79947bb696
• Download URL:
  https://stacks.cdc.gov/view/cdc/174802/cdc_174802_DS1.pdf
• File Type:
  [PDF - 1009.65 KB ]