Re: st: RE: Backed Up Iteration

[Nick Cox <njcoxstata@gmail.com>]

I can't really add to what I said previously, but the diagnosis that
the model is too much of a strain for the data remains in play. The
Statalist FAQ advises that you give precise code and precise results
for precise advise and I can only repeat that there.

Nick

On Thu, Jan 26, 2012 at 2:54 AM, Anna-Leigh Stone
<alstone@crimson.ua.edu> wrote:

> I am lead to believe the model is suited for the data. I was able to
> run the exact same code with a similar dataset a month ago and
> everything ran well. It is something within this dataset. It has the
> same number of variables but 3 times the number of observations as the
> other dataset that I ran. Could that be the issue? I tried simplifying
> the model and it run when there are 3 out of 15 of the variables but
> when I add a fourth variable regardless of which variable I add it
> gets hung up again.
>
>
> On Wed, Jan 25, 2012 at 2:57 PM, Nick Cox <n.j.cox@durham.ac.uk> wrote:
>> Often and often. It is very difficult to tell from this kind of report whether you are trying to fit a model that is a bad idea for your data or the fitting process is just a bit tricky (or both). As you have several predictors, fitting an overcomplicated model really is a possibility, whatever the scientific (or non-scientific, e.g. economic) grounds for wanting to use them all. You could try tuning the -ml- engine by e.g. changing -technique()-. Simplifying the model first and then introducing complications gradually can sometimes isolate problematic predictors.


Anna-Leigh Stone

>> I am using Stata 12.0 and I am attempting to run a fractional probit
>> regression with the command: glm dependent independent, fa(bin)
>> link(probit) cluster(gck). I have made sure that the dependent
>> variable values are not negative. I have 1500 dependent variable
>> observations out of 69,900 that fall at 0 and 1. Regardless of whether
>> I leave in the 0 and 1 values or take them out, I get the same log
>> likelihood iteration followed by backed up. It continues like this and
>> does not converge until I break it.
>> Has anyone else had this problem and know a solution to it? I do have
>> several variables but they are all necessary to my regression. I have
>> also tried the difficult option but that does not work either.

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