This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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9
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Type:
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Invited
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Date/Time:
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Sunday, August 1, 2010 : 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 - #305936 |
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Title:
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Imputing with Confidence
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Author(s):
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Andew Gelman and Jennifer Hill*+ and Yu-Sung Su and Jingchen Liu and Sonia Todorova
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Companies:
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Columbia University and New York University and Columbia University and Columbia University and Carnegie Mellon University
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Address:
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, , NY, 10003,
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Keywords:
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Abstract:
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Multiple imputation of missing data is generally recognized to be better than the usual alternatives of complete-case analysis, available-case analysis, and mean imputation. But multiple imputation requires a probability model (or, at least, a probabilistic algorithm). In typical applications, little effort is made to check the fit of the model, either to data or to external knowledge that can be used to judge whether the imputations make sense. We are working on graphical methods comparing observed to imputed data to diagnose problems with imputations. The goal is to build confidence in multiple imputations that will be used for later analysis.
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