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Abstract Details
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Activity Number:
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51
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Type:
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Invited
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Date/Time:
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Sunday, July 31, 2011 : 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 - #300090 |
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Title:
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Cleaning and Using Administrative Lists: Enhanced Practices and Computational Algorithms for Record Linkage and Modeling/Editing/Imputation
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Author(s):
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William Erwin Winkler*+
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Companies:
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U.S. Census Bureau
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Address:
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4600 silver hill road, suitland, MD, 20746,
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Keywords:
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quality ;
merging ;
computational algorithms
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Abstract:
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Administrative lists offer great opportunity for analyses that provide quantities for policy decisions. This is particularly true when groups of administrative lists are combined with survey and other data. To produce accurate analyses, data need to be cleaned and corrected according to valid subject matter rules. This paper describes methods and associated computational algorithms that, while often being easier to apply, are sometimes 40-100 times as fast as classical methods. This means that large administrative files can be cleaned (via modeling/edit/imputation) to eliminate contradictory or missing quantitative data to yield valid joint distributions, unduplicated within files, and matched and merged across files in a matter of days or weeks.
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Authors who are presenting talks have a * after their name.
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