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st: RE: RE: GLM Binomial family logit link postestimation GOF


From   "Martin Weiss" <[email protected]>
To   <[email protected]>
Subject   st: RE: RE: GLM Binomial family logit link postestimation GOF
Date   Mon, 24 May 2010 13:03:44 +0200

<>

To model proportions, also see Kit`s Stata tip at
http://www.stata-journal.com/article.html?article=st0147


HTH
Martin


-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Nick Cox
Sent: Montag, 24. Mai 2010 12:58
To: [email protected]
Subject: st: RE: GLM Binomial family logit link postestimation GOF

I suggest that degrading your proportions to binary makes very little
statistical sense for such analyses. You are just throwing away most of
the information. 

You can get observations and predictions as proportions. That leaves
scope for various diagnostic plots and even conventional R-square
calculations. 

For example, check out some of the ideas at 

http://www.stata.com/support/faqs/stat/rsquared.html

Nick 
[email protected] 

Venkatachalam, Alicia

I have just run a GLM under the binomial family with a logit link with a
proportion as my outcome. I am now unsure how best to test the GOF of
this model? I have read in the literature it is often best to rerun the
model as a logistic model and then use the available post estimation
commands, however because my outcome is a proportion and not binary I am
unsure if this is permissible? Should I recode my outcome as binary or
is there a way to run post estimation after my GLM model?


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