Just to be a little more clear: spatial effects in qualitative data
regression models are UGLY UGLY things...and no one has many good solutions
yet (though a few people are working furiously on it).

Basically, in any sort of qualitative data model, such as a possion model -
where your observed dependent variable is a count of a
occurrence/nonoccurence of some event - the observed process is not where
the spatial effect would/should be modeled.  These regressions are called
latent, because there is some underlying process (that we do not observe)
that is generating the qualitative outcome.

For this reason, any spatial autocorrelation would be part of this latent,
unobserved process, not necessarily corresponding one-to-one to the observed
outcome.

Kurt Beron and Wim Vijverberg of U Texas, Dallas, have a chapter coming out
in the new Anselin spatial econometrics book (should come out this year),
New Advances in Spatial Econometrics, that has a really good and careful
review of spatial effects in probit models, and how difficult it is to
specify a full covariance structure taking these into account.

As I mentioned, Dan Griffith of Syracuse is working on poisson models.  I
think Harry Kelejian (Dept of Economics, Maryland) has developed a TEST for
autocorrelation in possion models (but no correction).

You say you have thousands of polygons?  YIKES.  Beron and Vijverberg
developed a spatial probit estimator for 48 observations (or something like
that), and it takes several hours to run.  The nXn weighting
structure/incidental parameter problem makes it very hard to identify
anything that big.

Anyway - suffice to say - there is no COTS solution to your problem.  If you
find something out there that I haven't already mentioned, please let me
know!

Best,
Darla Munroe



--                                       
*************************************** 
Darla Munroe, Ph.D.                     
Postdoctoral Fellow                     
Center for the Study of Institutions,   
Population, and Environmental Change     
Indiana University
408 N. Indiana
Bloomington, IN 47408                      
[EMAIL PROTECTED]                     
php.indiana.edu/~dmunroe 
                                         



-----Original Message-----
From: Ben Wheeler [mailto:[EMAIL PROTECTED]]
Sent: Thursday, July 19, 2001 7:49 AM
To: [EMAIL PROTECTED]
Subject: AI-GEOSTATS: Spatial poisson regression software?


Dear all,

Please forgive the newbie style question...I've looked on the website 
at software listings and can't quite work out what I'm after.

I'm running poisson regressions for a large number of small areas 
(several thousand contiguous polygons) - predicting counts of events 
with several predictor variables for each small area. I'd like to be 
able to adjust these models to account for spatial autocorrelation. 
Does anyone know of software (ideally free/cheap) that will do this in 
a reasonably straightforward way? Either stand-alone or as an add-on to
Arc/info or arcview. I can also use Stata, SAS, SPSS etc.

Any ideas much appreciated,

Thanks a lot

Cheers
Ben


-------------------------
Ben Wheeler
MRC Research Student
Department of Social Medicine
University of Bristol
UK

e-mail [EMAIL PROTECTED]
-------------------------


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