Analyzing multiply imputed datasets: separate or stacked

Philip Greenwood (philip.greenwood@mcri.edu.au)
Additional contact information
Philip Greenwood: Clinical Epidemiology and Biostatistics Unit, Murdoch Childrens Research Institute, Melbourne

No 8, Australasian Stata Users' Group Meetings 2004 from Stata Users Group

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.

References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:boc:osug04:8

Access Statistics for this paper

More papers in Australasian Stata Users' Group Meetings 2004 from Stata Users Group Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum (baum@bc.edu).