Re: st: Problem with variables in glamm

[Richard Williams <richardwilliams.ndu@gmail.com>]

Actually, it sounds to me like Alice wants to run a fractional logit 
model, where the dependent variable ranges between 0 and 1. This 
could be for something like, say, proportion of employees who 
participate in a pension plan. glm can run such models (for non-panel 
data). But if you tried to run that same model with logit, all of the 
non-zero non-missing cases would get recoded to 1. I don't know 
gllamm but it sounds like gllamm may work more like logit that it 
does glm. Even if gllamm seems to be running I would want to make 
sure all the non-zero cases aren't getting recoded to 1.

At 07:30 AM 10/7/2013, William Buchanan wrote:
> If your dependent variable is binary (like it is implied by the info 
> you provide), then the only values it should take are 0 & 1.  Beyond 
> that it isn't exactly clear what your specific problem is. You 
> should also include the _exact_ syntax you enter and the exact 
> message/output provided by Stata.
>
> Sent from my iPhone
>
> > On Oct 7, 2013, at 6:53, "Alice Dalton (MED)" <A.Dalton@uea.ac.uk> wrote:
> >
> > Dear Statlist,
> >
> > I'm having a problem with the gllamm program (family(binomial) 
> link(logit)).
> >
> > 1. My dependant variable (a proportion) will only work if the 
> variable contains a zero, otherwise I get an r(2000) (no observations) error
> >
> > 2. Adding binary explanatory variables (eg a health variable 
> where 1 excellent, 0 not excellent) results in the message 
> 'variables have been dropped, can't continue' and an r(198) error. 
> The null model works; the null model works with continuous 
> variables added in; the null model plus one or more binary variables fails.
> >
> > The command I am using is     gllamm  [depvar] [varlist], 
> i(ParticipantId) family(binomial) link(logit). I have 276 cases and 
> 129 variables (not all of which are added to the model).
> >
> > If anyone with experience of gllamm has an idea of what is 
> happening here, I would be most grateful to hear it.
> >
> > Thank you!
> >
> > Alice Dalton
> >
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-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
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