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Re: st: A correlation matrix after multiple imputation


From   Richard Williams <richardwilliams.ndu@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: A correlation matrix after multiple imputation
Date   Fri, 23 Jul 2010 21:50:21 -0500

At 01:24 PM 7/23/2010, Alan Acock wrote:
Some journals request a correlation matrix and vector of standard deviations. The American Psychological Association stresses this in their journals. When doing multiple imputations, I'm unclear how to proceed.
...
4. I've seen manuscripts where people say here is the correlation matrix (casewise) before the multiple imputation, but this seems to be inconsistent with the entire logic of doing multiple imputation.

One rationale for presenting means/correlations/standard deviations is that it provides a means by which people could replicate your regression analyses without having the full data set. Of course, that isn't true anymore once you use MI. I kind of like option 4, because at least you are still getting descriptive measures. I suppose a critical issue, though, is how do the casewise statistics compare with the MI statistics?

My own personal intuition is that I should be happiest with MI when it increases my N, reduces the standard errors, and makes more of the effects significant. If, however, I start seeing sign flips or major differences in my substantive conclusions, then I feel more nervous. Perhaps my intuition is wrong though?


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Richard Williams, Notre Dame Dept of Sociology
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