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# Re: st: too good to be true : lr test in mlogit?

 From Maarten Buis To statalist@hsphsun2.harvard.edu Subject Re: st: too good to be true : lr test in mlogit? Date Fri, 13 May 2011 10:43:14 +0200

```On Fri, May 13, 2011 at 10:12 AM, John Litfiba <cariboupad@gmx.fr> wrote:
> 1) It is normal to obtain such a negative log likelihood when we use
> very large sample, right ? (n=2 millions here)

Yes, that is perfectly normal. It is the log of the probability of
observing the data given the parameters. This probability is the
product of the probabilities of observing each individual given the
parameters (assuming independent sampling...). A probability is a
number between 0 and 1, so the product of two such probabilities
results in a smaller number than either of the individual
probabilities. Do that multiplication 2 million times and you end up
with an extremely tiny number indeed. Take the log of such a tiny
number and you end up with a very negative number.

> 2) if the association (for example given by tabulation) show that
> there is strong association between yvar and xvar1 then it is
> plausible to obtain this fastastic LR statistic of... 140000 ??

I would not call that fantastic. It just test whether the effects of
all covariates are all equal to 0, so you would expect that with such
a large sample size you would thoroughly reject that hypothesis, which
you do.

Hope this helps,
Maarten

--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

http://www.maartenbuis.nl
--------------------------
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