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Re: st: mlogit problem

From   "JVerkuilen (Gmail)" <>
Subject   Re: st: mlogit problem
Date   Sun, 17 Feb 2013 23:29:57 -0500

On Sun, Feb 17, 2013 at 7:31 PM, saqlain raza <> wrote:
> Thanks JVerkuilen for your response. N=360.

For regression models it's good practice to maintain a minimum of
10-20 observations per parameter, which is ordinarily the number of
variables. With mlogit, you need to multiply the number of variables
by K-1 where K is the number of categories because there is a
parameter for each category by variable combination, less the
reference category. Even so I'd err on the high side. Thus I'd suggest
with your data you can afford something like 6-12 variables to have a
chance at having reasonably well-defined coefficients with sensible
asymptotic standard errors given your sample size.

Even when your model is running, the parameters must be completely
wonky. If the standard errors are huge that's a sign.

Yes I want to do variables selection for my study. If this is not a
good idea, what should I do?
> Thanks again for your cooperation

Others have addressed this point as well as I think is even possible.
You're hoping for a miracle.

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