Abstract
In this chapter, I provide step-by-step instructions for performing multiple imputation and analysis with SAS version 9. I describe the use of PROC MI for multiple imputation but also touch on two other ways to make use of PROC MI for handling missing data when hypothesis testing is not the issue: (a) direct use of the EM algorithm for input into certain analysis programs, and (b) generating a single data set imputed from EM parameters.
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- 1.
Note that the variable Program, used in the Proc Mixed example near the end of the chapter, is a simulated program variable, and results based on that variable are somewhat different from true program effects observed for the AAPT project.
- 2.
Note that in most of these preliminary PROC MI runs, I am setting NIMPUTE = 2. Please do not take from this that I ever think just two imputations is enough. I am using NIMPUTE = 2 for these preliminary runs to save time. When it matters, NIMPUTE will be set to a reasonable number.
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Graham, J.W. (2012). Multiple Imputation and Analysis with SAS. In: Missing Data. Statistics for Social and Behavioral Sciences. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4018-5_7
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