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RE: st: Chow test


From   "Kaganova, Yevgeniya" <ykaganova@rti.org>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Chow test
Date   Thu, 1 Apr 2010 09:08:51 -0400

Thank you very much! 

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Clive Nicholas
Sent: Thursday, April 01, 2010 1:18 AM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Chow test

Yevgeniya Kaganova wrote:

> Dear Statalisters, we want to justify that we can run a single model 
> with 3 groups of people in it (normal weight, overweight, and obese 
> people). We are generating coefficients on all vars for each group, 
> then just want to test our "disabled" variable across all the 3 groups 
> in the model post-estimation to see if different across the groups. 
> The testing for 3 groups is done the way it is explained in here 
> http://www.stata.com/support/faqs/stat/chow3.html
>
> But the model we are running is GLM Y  X  if Y>0  family(gamma)
> link(log) . So the coefficients are logged. Is it OK to do is the same 
> way as it is done for the OLS. Can we test the 3 "disabled" 
> coefficients without transforming them first back to normal (unlogged) 
> scale. Do we have to worry about smearing factors with this GLM specification?

Happily assuming that -glm- is the way to estimate your model, what's wrong with combining those three groups to make an ordinally-measured index variable, and then running your model with that? In the interests of model parsimony - and being really lazy - that's what I would do.

--
Clive Nicholas

[Please DO NOT mail me personally here, but at <clivenicholas@hotmail.com>. Please respond to contributions I make in a list thread here. Thanks!]

"My colleagues in the social sciences talk a great deal about methodology. I prefer to call it style." -- Freeman J. Dyson.

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