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Abstract Details
Activity Number:
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305
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 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 - #302643 |
Title:
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Propensity Score Adjustment for Nonignorable Nonresponse
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Author(s):
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Minsun Kim Riddles*+ and Jae-kwang Kim
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Companies:
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Iowa State University and Iowa State University
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Address:
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Department of Statistics, Ames, IA, 50011-1210,
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Keywords:
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missing data analysis ;
nonparametric prediction ;
generalized least squares ;
EM algorithm
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Abstract:
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The propensity score adjustment method is commonly used to adjust the bias that is due to nonresponse. We consider the propensity score adjustment method under nonignorable nonresponse. The method we propose does not use a full parametric distributional assumption, but it leads to consistent estimation of the parameters with some moment assumptions. We used the generalized least squares method to combine the observed information and compute an optimal estimator. Variance estimation is discussed, and results from limited simulation studies are presented to show the performance of the proposed method.
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