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Re: st: summary statistics with mi multiple imputation


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
> 
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