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Abstract Details
Activity Number:
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189
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Type:
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Contributed
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Date/Time:
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Monday, August 1, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section for Statistical Programmers and Analysts
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Abstract - #301651 |
Title:
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A Single-Imputation SAS Macro
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Author(s):
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Xingshu Zhu*+ and Shuping Zhang
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Companies:
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Merck & Co., Inc. and Merck & Co., Inc.
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Address:
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351 N. Sumneytown Pike, North Wales, PA, 19454,
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Keywords:
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missing data ;
imputation
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Abstract:
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The problem of missing data arises in many clinical trials, and practical research fields. Imputation is often required to replace the missing value of a variable in a dataset such the "completed" data set can be used in subsequent analyses of the data. When working with an extensive dataset containing millions of records, however, it would be highly impractical, or maybe even impossible, to use the multiple imputation method because of the overwhelmingly large number of datasets that would have to be created. In this paper, we introduce a simple SAS macro that allows the user to create a "complete" SAS dataset through single imputation by selecting different statistical methods.
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