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Activity Number:
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265
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2008 : 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 - #301695 |
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Title:
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Extension of Fractional Imputation to General Missingness Patterns using Maximum Likelihood
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Author(s):
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Minhui Paik*+
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Companies:
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Iowa State University
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Address:
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, , ,
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Keywords:
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missing data ; imputation ; replicate variance estimation
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Abstract:
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Surveys frequently have missing values for some variables for some units. Imputation is a widely used method in sample surveys as a method of handling missing data problem. We provide an new imputation procedure for various imputation models retaining many of the desirable properties of model-based imputation estimation and hot-deck imputation under fractional imputation. The main objective of this procedure is to construct an easy-to-use data set for general purpose estimation. We provide an extension of fractional imputation methods to general patterns of missing data via maximum likelihood calibration.
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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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