Maarten,
It seems that I have multicollinearity with some of the variables; so I made dummy variables for these variables and include these instead of the original variables in the model. It seems to be working thus far.
Thanks for replying back.
Dale
Dale Hardy, PhD RD CDE CHES
Research Associate
University of Texas School of Public Health
Houston, TX 77030
Phone: (713) 500-9221
Fax: (713) 500-9264
Email: [email protected]
________________________________________
From: [email protected] [[email protected]] On Behalf Of Maarten buis [[email protected]]
Sent: Wednesday, February 03, 2010 9:01 AM
To: [email protected]
Subject: Re: st: xtmelogit model not converging
--- On Tue, 2/2/10, Hardy, Dale S wrote:
> I am running a logistic mixed model and the performing
> gradient-based optimization iterations are not concave, so
> the model is not converging. Can you tell me what can be
> wrong? How can I fix it?
The standard advise is to simplify the model, so remove the
random coeficient for race, if that model converges you can
try a model with random coefficient for race, if that model
converges you can try to relax the covariance between the
random coefficients by adding the -covariance(unstructured)-
option.
-- Maarten
--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://www.maartenbuis.nl
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