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RE: st: How do I drop incomplete observations after running multiple imputation?


From   "Wilson, Kimberly J" <Kimberly.J.Wilson@uth.tmc.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: How do I drop incomplete observations after running multiple imputation?
Date   Wed, 7 Nov 2012 13:49:56 -0600

I went down that route originally without success, but I'm glad you suggested it.
Realized I needed to create the dummy as a passive variable, not regular.
Success!

Thank you.

Kim

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of JVerkuilen (Gmail)
Sent: Wednesday, November 07, 2012 1:32 PM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: How do I drop incomplete observations after running multiple imputation?

On Wed, Nov 7, 2012 at 2:22 PM, Wilson, Kimberly J <Kimberly.J.Wilson@uth.tmc.edu> wrote:

>  I somehow need to drop the observations from the imputed data that still contain missing data so that my sample is constant across the models.  Without doing so, I have 1,854 obs in the first two models, 1841 in the third, and 1835 in the fourth.  I want the sample to be 1835 across all four models.
>
> To drop the observations with missing values in the imputed data, I have tried various iterations of the following:

If it's only a few cases you want to drop, why don't you simply make a dummy variable with those cases and drop based on that? Simple and brute force, but it works. You can also simply use if to make for a consistent sample without dropping those cases completely.

Jay

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