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st: RE: GLM Binomial family logit link postestimation GOF

From   "Nick Cox" <>
To   <>
Subject   st: RE: GLM Binomial family logit link postestimation GOF
Date   Mon, 24 May 2010 11:58:06 +0100

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

For example, check out some of the ideas at


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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