Hi Kevin,
I think your best bet will be to drop some of the random effects, but you
could keep the fixed effects. Graphing the data may help decide which to
drop, but I have also found, with a standard -logit-, that comparing the
standard errors with and without the -cluster()- option seems to be a good
place to start. The variables with an increase in the SE with -cluster-
seem to be the ones where a random effect most improves model fit.
Hope that helps,
Cam Gillies
Thanks.I will try to kick some of them out so at least I can test if my
model is
feasible.
Kevin
ÒýÓÃ Nick Cox <[email protected]>:
> The simple answer is that this won't help. You
> are fitting a very difficult model and changing the memory
> won't make it less difficult. You might get results
> faster, at best, but the answer will be the same.
>
> Nick
> [email protected]
>
> Xiaoheng Zhang
>
> > Dear Anders,
> >
> > In my sample there are 12 countries as an alternative set and
> > total 2076
> > observations(173 firms*12 countries).Frankly I am reluctant
> > to remove any one of
> > them from the alternative set.Could I set a large memory for
> > Stata to tackle
> > this problem.Currently the memory allocated to Stata is 100mb
> > and the dataset is
> > far smaller than 100mb.
>
>
> Anders Alexandersson <[email protected]>:
>
> > > Kevin (Xiaoheng Zhang <[email protected]>) wonders why overflow
> > can happen
> > > when using gllamm for a location choice problem:
> > >
> > > > I am running a multilevel regression model by -GLLAMM-.The initial
> > > > results are good but then the program reports "overflow
> > at level 1 (173
> > > > missing values)".It keeps reporting this msg for a long
> > time.Anyone has a >
> > > hint about this? [...] For you information,my command are
> > > > -gllamm location eatr cdrug2 dist ap sisters2 wage3 edu3
> > cai share if
> > > > highgrow==1&deudmy==0, nocons expand(id choice o) i(parentid2)
> > > > lin(mlogit) family(binom) nrf(10) eqs(eatr cdrug2 dist ap
> > sisters2 wage3
> > > > edu3 cai share cons) nip(8) trace adapt-
> > >
> > > I think that Stata's error message for numerical overflow,
> > r(1400), is
> > > helpful here, because gllamm uses numerical integration. The error
> > > description for r(1400) begins with this sentence: "You
> > have attempted
> > > something that, in the midst of the necessary calculations, has
> > > resulted in something too large for Stata to deal with accurately."
> > > Thus, I guess that if Kevin tries to estimate a simpler model, the
> > > message may disappear. Kevin, for example how many choice categories
> > > do you have? Try with fewer choice categories.
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
*
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*
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