JSM 2011 Online Program

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Abstract Details

Activity Number: 189
Type: Contributed
Date/Time: Monday, August 1, 2011 : 10:30 AM to 12:20 PM
Sponsor: Section for Statistical Programmers and Analysts
Abstract - #301651
Title: A Single-Imputation SAS Macro
Author(s): Xingshu Zhu*+ and Shuping Zhang
Companies: Merck & Co., Inc. and Merck & Co., Inc.
Address: 351 N. Sumneytown Pike, North Wales, PA, 19454,
Keywords: missing data ; imputation
Abstract:

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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