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


From   Woolton Lee <finished07@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: robust standard errors, sureg, & suest
Date   Thu, 27 Aug 2009 12:19:59 -0400

If suest doesn't work after sureg, is there some way I can recover
robust standard errors for the sureg regressions I am planning to run?

Woolton

On Thu, Aug 27, 2009 at 10:34 AM, Schaffer, Mark E<M.E.Schaffer@hw.ac.uk> wrote:
> 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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>
>
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