I'm hoping to get some pointers to useful citations to satisfy an editor's concerns on our use of multiple imputation (using NORM). Here are the two issues:
"However, I could be persuaded by citations (to publications by imputation experts) or evidence (e.g., from Monte Carlo studies) showing that: (a) it is acceptable to impute missing data on the outcome variable; (b) 40% falls within the acceptable range for data imputation."
I understand that (a) is not only acceptable, but obligatory in a covariance analysis, because a covariance matrix makes no distinction between outcomes and anything else. However, this is so fundamental, I'm not finding explicit statements of it in my sources. For (b), I realize that it's fraction of missing information that's the issue. We used 10 imputations, so we should be in good shape for the missingnes we have, but are there any good simulation studies varying the missing information and showing satisfactory results? Schafer (97) talks about rates up to 90% just increasing the number of iterations needed, but there's not much detail on performance.
In other words, has anyone written, "Multiple imputation for content journal editors" yet?
Thanks, Pat Malone
-- Patrick S. Malone, Ph.D., Research Scholar Duke University Center for Child and Family Policy Durham, North Carolina, USA e-mail: [EMAIL PROTECTED] http://www.duke.edu/~malone/
