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RE: st: robust standard errors, sureg, & suest


From   "Schaffer, Mark E" <M.E.Schaffer@hw.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: robust standard errors, sureg, & suest
Date   Thu, 27 Aug 2009 15:34:51 +0100

Just wondering ... does -suest- work after -sureg-?  -suest- needs scores but I'm not sure -sureg- can deliver them.

--Mark

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu 
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of 
> Austin Nichols
> Sent: 27 August 2009 15:14
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: robust standard errors, sureg, & suest
> 
> Woolton Lee<finished07@gmail.com> :
> I am just guessing that modeling covariances in the data well 
> at the imputation step will be crucial, and that you will 
> need a lot more imputations than usual, perhaps 100 instead 
> of 5 or 10.  Just guessing, as I say.  You should run your 
> own simulation--what is your data structure?  What are you imputing?
> 
> On Thu, Aug 27, 2009 at 10:02 AM, Woolton 
> Lee<finished07@gmail.com> wrote:
> > I am planning to estimate a multi equation model using multiply 
> > imputed data (5 imputations).  I plan to use sureg and mim then use 
> > suest to recover robust standard errors for the parameter estimates.
> > I am assuming this will work from what I've read in the 
> help file but 
> > I am not certain if there are problems to implementing this 
> plan that 
> > I haven't anticipated.  Could someone please confirm that as far as 
> > implementing my idea, it will work?  Thanks.
> >
> > I believe one problem with what I've planned is that combining 
> > multiply imputed estimates using sureg may not be 
> guaranteed to yield 
> > statistically valid results - there may not have been any 
> simulation 
> > studies to verify that this approach to estimation will be unbiased 
> > and consistent, etc.  If there is anyone that can comment 
> on this as 
> > well please do.
> >
> 
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