well the only measure I can think of as really a FIT measure is how
many observations were classified appropriately to their 0/1
categories. With random effects, you don't even have a predicted
probability -- at least marginally, unless you are willing to
integrate out the random effects.
Within GLM framework, there are some reasonable goodness of fit
measures based on deviance and residuals of different kind. Again,
that has an i.i.d. consideration in mind.
What are you going to use this measure for?
On Thu, 07 Oct 2004 19:09:22 +0200, Uwe Berberich <[email protected]> wrote:
> Stas,
>
> thanks for your reply. Do you have any suggestions for better goodness
> of fit measures in probit regressions on panel data? McFadden R2 or
> Pseudo R2 were the ones suggested in various sources and empirical
> studies but I'm open for whatever turns out to be useful and meaningful.
> I'm just puzzled that *xtprobit* does not return any measure at all. Is
> there any theoretical motivation why I could report probit results
> without any goodness of fit measure?
>
> Thank you very much
> uwe
--
Stas Kolenikov
http://stas.kolenikov.name
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