A Comparison of Design-Based and Calibrated-Bayes Estimates Using Data from a Health Survey

• Activity Number: 249
• Type: Contributed
• Date/Time: Monday, August 5, 2013 : 2:00 PM to 3:50 PM
• Sponsor: Survey Research Methods Section
• Author(s): Meena Khare*+ and Hee-Choon Shin and Alena S. Maze
• Companies: NCHS/CDC and National Center for Health Statistics and NCHS/CDC
• Keywords: Bayesian ; Complex surveys

Abstract

Bayesian methods have been gaining popularity as an alternative to the traditional design-based methods for estimation from complex surveys. In this paper, we apply Calibrated-Bayesian methods to estimate vaccination rates from the National Immunization Survey (NIS). NIS is a large telephone survey, which has been continuously conducted to monitor childhood vaccination coverage among U.S. children aged 19-35 months since 1994 (http://www.cdc.gov/nchs/nis.htm). Official design-based vaccination coverage rates at the national, state, and selected urban area levels estimated using data from the NIS are available at the Website http://www.cdc.gov/vaccines/stats-surv/nis/default.htm#nis. Data from the recent NIS public-use files are used to compute and compare the Bayesian estimates with the design-based estimates. We also compare sub-domain estimates based on the two methods by selected demographic characteristics.