st: RE: mlogit problem with "predict"

[Sheela Athreya <athreya@neo.tamu.edu>]

Maarten, many thanks for your helpful response.  As soon as I posted  
the message I wished I had clarified what the variables pc1-pc4 were.

------Maarten Buis wrote:


> Are pc1 - pc4 dummy variables for a single categorical variable  
> (called pc)?
They are quantitative variables--principal component scores from my  
original data set, which consisted of a series of measurements taken  
on a set of human skulls that make up my cases (I'm an  
anthropologist, lest that sounds too morbid).

I ran PCA in order to reduce the variables and address the fact that  
measurements taken on the skull are not independent.  Running PCA  
allows me to work with orthogonal data.


> What you are looking for are (almost) empty cells, and (almost)  
> perfect
> predictions, or anything else that looks odd. It's pretty hard to
> explain what it is that makes such a table look "odd", other than if
> something is really wrong it is usually pretty obvious (though not
> always).
>
> I propose an incremental approach: See if you can solve the problem
> by looking at -tab tax pc-, and report back to us. If that solves the
> problem, great, if not, we'll try something else. (Notice that we are
> living in different time zones, so it might take some time before I
> get back to you, but somebody else on the Statalist might jump in)
The idea that maybe I have an (almost) perfect prediction occurred to  
me too, but I don't know how to investigate it. Perhaps there is an  
equivalent test to -tab tax pc- that allows me to look at  
quantitative variables for anything that is off?

Thanks again,
Sheela


*******************************
Sheela Athreya, Ph.D.
Texas A&M University
4352 TAMU
College Station, TX  77843
phone: 1-979-845-4785
fax: 1-979-845-4070



> > Hello,
> >
> > I am using Stata 9 for the PC, and have run the following command:
> >
> > mlogit tax pc1 pc2 pc3 pc4, vce(jackknife)
> >
> > Where (tax) has five outcomes
> >
> > The regression results seem to be fine, but when I then try to run  
> > "predict p1 p2 p3 p4 p5" to obtain posterior probabilities, I get  
> > the following:
> > "p1: 27 missing values generated"  (note: there are more than 27  
> > cases in the data set)
> >
> > And the resulting  posterior probabilities are completely off-- 
> > every value of p1 is either 0, 1 or missing  (".")
> > And, for a handful of cases, the values of p1-p5 are *all* 0.
> >
> > This also happens when I do not use the vce(jackknife) command,  
> > and when I use three instead of four independent variables.
> >
> > I suspect something is wrong among my cases (or variables) such  
> > that maybe two of my groups are so highly correlated that I am  
> > getting these results?  But I am not familiar enough with the  
> > principles of multinomial logit to know.  Any help or advice would  
> > be much appreciated.
> >
> > Many thanks,
> >
> >
> > *******************************
> > Sheela Athreya, Ph.D.
> > Texas A&M University
> > 4352 TAMU
> > College Station, TX  77843
> > phone: 1-979-845-4785
> > fax: 1-979-845-4070


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