Abstract Details
Activity Number:
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249
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Type:
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Contributed
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Date/Time:
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Monday, August 5, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Survey Research Methods Section
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Abstract - #308457 |
Title:
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A Comparison of Design-Based and Calibrated-Bayes Estimates Using Data from a Health Survey
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Author(s):
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Meena Khare*+ and Hee-Choon Shin and Alena S. Maze
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Companies:
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NCHS/CDC and National Center for Health Statistics and NCHS/CDC
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Keywords:
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Bayesian ;
Complex surveys
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Abstract:
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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.
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Authors who are presenting talks have a * after their name.
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