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Activity Number: 653
Type: Contributed
Date/Time: Thursday, August 7, 2014 : 10:30 AM to 12:20 PM
Sponsor: Survey Research Methods Section
Abstract #312893
Title: An Application of Calibrated Bayes Methods to Estimate Vaccination Coverage Rates from the NIS
Author(s): Meena Khare*+ and Philip J. Smith and Alena Maze
Companies: NCHS/CDC/DHHS and CDC and NCHS
Keywords: Bayesian ; Complex surveys
Abstract:

Bayesian methods can be used as an alternative to the traditional design-based methods to improve precision of small sub-domain estimates from complex surveys. Calibrated Bayesian methods use the design and weighting structure of complex surveys. We apply calibrated Bayesian methods to estimate state-specific vaccination coverage rates from the National Immunization Survey (NIS), a large telephone survey used to monitor childhood vaccination coverage among U.S. children 19-35 months. We use NIS data from 2010-2011 and use model-based distribution of predicted values of vaccination coverage as an informative prior to simulate posterior probability distributions. Estimates from these posterior distributions are then compared with the corresponding design-based official state-specific vaccination coverage estimates and their variances. We also compare the state-specific sub-domain Bayesian estimates by selected demographic characteristics with those obtained using small-area estimation methods. Evidence of improved precision would lead to consideration to apply calibrated Bayesian methods for small sub-domain estimates for future analyses.


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