During the analysis of the International PIRLS project, a comparative study on reading comprehension of students of Grade 4 and 5, the following problem was encountered during the analysis phase:
Some of the dependent variables (the plausible scores) are obtained by doing multiple impution on several scores (5 times). Usually, properly analyzing the data sets resulting from multiple imputation makes it necessary to do the analysis of each data set separately and then afterwards, combining the results in some way (as far as I know, the only standard statistical package that does this for you automatically, is Mplus).
However, in case the dependent variable is imputed, one can use a repeated measurement design. In the case described above, an extra level was added to a multilevel analysis with the 5 plausible scores as a repeated measurement.
Drawback of this approach in multilevel analysis (MLwiN) is that the data sets which are already enormous in this case, are quintupled.
Herman
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3 comments:
Pooling of results can also be very easily done with MICE for R.
See for example
http://www.stefvanbuuren.nl/publications/MICE%20in%20R%20-%20Draft.pdf
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