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Analyzing multiply imputed datasets: separate or stacked

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  • Philip Greenwood

    (Clinical Epidemiology and Biostatistics Unit, Murdoch Childrens Research Institute, Melbourne)

Abstract

The method of multiple imputation provides an attractive approach to handling missing data in large studies. A variety of software is now available to produce multiply imputed (MI) datasets, and we have published a set of Stata commands a"MI tools" that facilitate the manipulation and analysis of MI datasets. MI datasets can be either a set of separate data files or a single (stacked) data file with some extra information to index the datasets. For the purpose of writing Stata commands to analyze these data, what are the benefits of each format? The stacked format seems to offer greater efficiency and elegance and can make better use of existing syntax structures. However, separate data files seem to offer greater overall flexibility and some important tasks can only be implemented in that format. It seems that a combined approach might give the best of both worlds. This talk will describe our current work on a revised version of MI tools.

Suggested Citation

  • Philip Greenwood, "undated". "Analyzing multiply imputed datasets: separate or stacked," Australasian Stata Users' Group Meetings 2004 8, Stata Users Group.
    • Handle: RePEc:boc:osug04:8
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