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Activity Number:
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292
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Type:
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Invited
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Date/Time:
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Tuesday, August 5, 2008 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Survey Research Methods
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| Abstract - #300260 |
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Title:
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Can Calibration Be Used To Adjust for 'Nonignorable' Nonresponse?
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Author(s):
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Phillip S. Kott*+ and Ted Chang
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Companies:
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National Agricultural Statistics Service and University of Virginia
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Address:
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3251 Old Lee Highway, Fairfax, VA, 22030,
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Keywords:
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prediction model ; quasi-randomization ; benchmark variable ; model variable ; bias ; response-guided response group
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Abstract:
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Calibration can be used to adjust for unit nonresponse when the model variables on which the response/nonresponse mechanism depends do not coincide with the benchmark variables in the calibration equation. As a result, model-variable values need only known for the respondents. This allows the treatment of what is usually considered nonignorable nonresponse. Although one can invoke either quasi-randomization or prediction-model-based theory to justify the calibration, both frameworks rely on unverifiable model assumptions, and both require large sample to produce nearly unbiased estimators even when those assumptions hold. We will explore these issues theoretically and with a small empirical study.
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