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Abstract Details
Activity Number:
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66
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Type:
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Topic Contributed
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Date/Time:
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Sunday, July 29, 2012 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Survey Research Methods
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Abstract - #304130 |
Title:
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Small-Area Estimation Combining Information from Several Sources
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Author(s):
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Seunghwan Park*+ and Seo-young Kim and Jaekwang Kim
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Companies:
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Seoul National University and Statistics Korea and Iowa State University
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Address:
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SAN 56-1, Sillim-Dong, Gwanak-Gu, Seoul, International, , South Korea
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Keywords:
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synthetic estimation ;
measurement error ;
two-phase sampling ;
generalized least squares ;
area level model
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Abstract:
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Combining information from different source is an important practical problem. The source of information can come from a probability sampling with direct measurement, from another probability sampling with indirect measurement, or from auxiliary area level information. We consider the area-level model approach to small area estimation with at least two survey information. The way we combine information is based on the generalized least squares estimation from the measurement error model, where the sampling error of the survey estimates of direct measurement can be treated as the measurement error. Mean square estimation is also discussed. The proposed method is applied to the Korean labor force survey problem.
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Authors who are presenting talks have a * after their name.
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