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Re: st: xtlogit: panel data transformation's recast to double makes model incomputable


From   "JVerkuilen (Gmail)" <[email protected]>
To   [email protected]
Subject   Re: st: xtlogit: panel data transformation's recast to double makes model incomputable
Date   Tue, 2 Apr 2013 14:06:34 -0400

It sounds like you're running into some kind of weird near but not
complete perfect prediction. If you look at the log-likelihoods in the
model they are frequently diverging:

> From A:
> log likelihood = -8.99e+307
> (initial step bad)

> From A and E (different likelihoods of course):
> log likelihood = -235698.21
> (backed up)

> From B, C and E:
> log likelihood =    -1.#INF
> (initial step bad)

So these fail simply on the face of as the first one is essentially
diverged to -Infinity and the third has as well. The middle is bad,
too, as "backed up" means that the step wasn't an improvement.

The IV that you want to use has some truly wicked properties. It is
quite possibly the most skewed variable I've seen in my career....

If you just run with the offending variables does it fail? When I say
"fail" I don't mean does it run to completion because that's a very
low standard, but do you get a ludicrous log-likelihood such as the
one there? Is the Hessian and parameter correlation matrix similarly
silly? I suspect it must be regardless of whether the model converges
or not.
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