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Abstract Details
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Activity Number:
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490
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Type:
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Invited
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Date/Time:
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Wednesday, August 3, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Survey Research Methods
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| Abstract - #300132 |
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Title:
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Bayesian Predictive Inference for Small Areas with Uncertain Unit-Level Models
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Author(s):
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Donald Malec*+ and Ryan Janicki
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Companies:
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Centers for Disease Control and Prevention and U.S. Census Bureau
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Address:
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National Center for Health Statistics, Hyattsvillle, 20782,
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Keywords:
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Abstract:
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Validation of a unit level model at the small area level may be difficult due to small sample size. In addition, the sample design may often be informative at this level and needs to be accounted for. Lastly, Bayesian inference requires a complete likelihood, necessitating the need for a detailed description of the small area likelihood. The consequences of knowing little about the sampling distribution beyond the first two moments, including the dependence between observations will be demonstrated.Criteria for choosing distributions will be discussed.
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