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Re: st: Imputing for missing proportions


From   Geomina Turlea <geomina@yahoo.fr>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Imputing for missing proportions
Date   Sat, 13 Apr 2013 00:03:40 +0100 (BST)

Thank you!


--- On Fri, 4/12/13, JVerkuilen (Gmail) <jvverkuilen@gmail.com> wrote:

> From: JVerkuilen (Gmail) <jvverkuilen@gmail.com>
> Subject: Re: st: Imputing for missing proportions
> To: statalist@hsphsun2.harvard.edu
> Date: Friday, April 12, 2013, 6:54 PM
> On Fri, Apr 12, 2013 at 5:44 AM,
> Geomina Turlea <geomina@yahoo.fr>
> wrote:
> > I know, but - mi impute- does not support glm either
> 
> Best advice I have is to logit transform the proportions and
> then use
> PMM, or just use PMM directly. You probably should try
> several
> different sets of assumptions about the imputation model,
> though. Nick
> is right, MAR is a stronger assumption than many people
> realize and
> harder to make plausible than one would suppose. Outliers
> are also a
> problem with MI approaches. MI spreads the effect all
> throughout the
> dataset.
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