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Activity Number:
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82
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Type:
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Invited
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Date/Time:
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Monday, August 4, 2008 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Survey Research Methods
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| Abstract - #300370 |
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Title:
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Examining Sensitivity of Small-Area Inferences to Uncertainty About Sampling Error Variances
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Author(s):
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William R. Bell*+
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Companies:
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U.S. Census Bureau
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Address:
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Room 5K142A, SRD, Washington, DC, 20233,
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Keywords:
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sampling error model ; Fay-Herriot model ; Bayesian inference ; small area estimation
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Abstract:
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Small area estimation based on area level models typically assumes that sampling error variances for the direct survey small area estimates are known. In practice we use estimates of the sampling error variances, and these can contain substantial error. This suggests modeling the sampling variances to improve them and to quantify effects of their estimation error on small area inferences. We review papers that have attempted to address these issues. We then provide some results on the latter issue, showing, in a simple framework, how error in estimating sampling variances can affect the accuracy of small area predictions and lead to bias in stated mean squared errors.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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