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| From | David Bell <dcbell@iupui.edu> |
| To | <statalist@hsphsun2.harvard.edu> |
| Subject | Re: st: summary statistics with mi multiple imputation |
| Date | Tue, 20 Jul 2010 09:35:51 -0400 |
-- Alan, One imagines that you do not have much missing data for your demographic variables. I would in general be inclined to give descriptive statistics on non-missing data only. This avoids any question from readers (and reviewers) about whether the imputation method introduced any biases. The non-missing data are are, of course, the sample from which imputations are to be made. If you include Ns, then readers can see how much data were imputed. Dave ==================================== David C. Bell Professor of Sociology Indiana University Purdue University Indianapolis (IUPUI) (317) 278-1336 ==================================== On Jul 19, 2010, at 5:35 PM, Alan Acock wrote: > When imputing 20 datasets and dong a logistic regression, I still need some descriptive statistics on background/demographic variables to describe the sample. > a. Should I report the demographic means/sd's for each variable using the original dataset and N for each variable? > b. Should I report the grand mean treating the 20 datasets as one big dataset? > c. What is the best practice? Is there a way to get confidence intervals that around the means that take the multiple imputation into account? > > Perhaps I'm missing something that is quite obvious. > > --Alan Acock > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/