Solved – Multiple imputation in SAS for longitudinal data

missing datamultiple-imputationpanel data

I have a data set from a repeated measurement study comparing two groups with missing data due to lost-to-follow-up (~20%).

I know how to apply multiple imputation method for cross-sectional data. For repeated measurement (longitudinal data) the situation is a lot more complex because we need to make use of the correlation between the Y values across time-points. STATA can do this using the ICE procedure http://www.ats.ucla.edu/stat/stata/faq/mi_longitudinal.htm. But I cannot work out how to do this in SAS. I am grateful if someone can help.

Best Answer

There is an SAS macro called MMI_IMPUTE specifically designed for MI of clustered data. In addition, Mistler (2013) has written a nice tutorial that shows how to use this macro. The article is available online and should be accessible to all.

Mistler, S. A. (2013). A SAS macro for applying multiple imputation to multilevel data. In Proceedings of the SAS global forum: 2013.

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