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st: RE: Polytomous vs "regular" unconditional logistic regression


From   "Kieran McCaul" <kieran@dph.uwa.edu.au>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Polytomous vs "regular" unconditional logistic regression
Date   Fri, 28 Nov 2003 11:02:06 +0800

I haven't used polytomous regression, but was under the impression that the
same results would be obtained from both approaches.

Do you have missing data?  If so, this would definitely result in different
answers.

> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu]On Behalf Of Roger Milne
> Sent: Friday, 28 November 2003 9:41 AM
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Polytomous vs "regular" unconditional logistic regression
>
>
> Hi,
>
> I don't understand why I get different estimates (ignoring
> standard errors)
> from the following two models:
>
> 1. Multivariate polytomous logistic regression, with outcome
> categories 0,
> 1 and 2 (with ", basecategory(0)")
> 2. Two separate multivariate (same covariates) "regular" logistic
> regression models:
>          (i)  with ", if outcome~=2"
>          (ii) with ", if outcome~=1"
>
> The "coeff" estimates are very different (eg.  -1.52 vs. -1.06)
>
> For the univariate case, I get the same estimates from 1 and 2, but they
> start to "diverge" as soon as I add an additional covariate.
>
> Thanks,
>
> Roger Milne.
>
> Roger Milne
> Research Fellow
> Centre for Genetic Epidemiology
> University of Melbourne
> Tel:  +613 8344 0803
> Fax: +613 9349 5815
> email: rlm@unimelb.edu.au
>
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>


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