st: xtnbreg, nbreg, and tests of assumptions

[Dalhia <ggs_da@yahoo.com>]

Hi,

I am trying to figure out whether I should use nbreg (with 
correction for autocorrelation and heteroskedasticity) or xtnbreg (with 
random effects)? My independent variable is count with significant overdispersion, and I have panel data (cross sectional time series). One of my main dependent variables is time invariant, and therefore I cannot use xtnbreg fixed effects. xtnbreg random effects is giving me some funny results that are hard to believe, but how should I decide which one I should be using (xtnbreg or nbreg)? Also, are there tests to check if the assumptions of these models are satisfied in my data?

Finally, I have two independent variables,  predicted by the same dependent variables. But I can't find a version of SUR appropriate for negative binomial. I am not really interested in cross-equation testing. If I don't do a seemingly unrelated regression, does that bias the coefficients or does it produce inefficient 
coefficients.

Thanks so much. I really appreciate your help.
Dalhia

--- On Wed, 12/15/10, Maarten buis <maartenbuis@yahoo.co.uk> wrote:

From: Maarten buis <maartenbuis@yahoo.co.uk>
Subject: Re: st: Difference between xtlogit, xtmelogit, gllamm
To: statalist@hsphsun2.harvard.edu
Date: Wednesday, December 15, 2010, 10:28 AM

--- On Wed, 15/12/10, Rajaram Subramanian Potty wrote:
> I have event history data and this data has been converted
> into discrete time to fit discrete time hazard model.
> Now, I want to fit a multilevel model. But there are: three
> different proceudres such as xtlogit, xtmelogit and gllamm.
> I want to know which procedure is more appropriate for
> analysing the discrete time data. 

All three will do for a basic multilevel model for the odds 
(not the hazard) of survival. If you want to model a 
multilevel model for the hazard of survival you can use 
-gllamm- with the cll link function. The difference between 
-xtlogit- and -xtmelogit- is that the latter can accomodate 
more complex multilevel structures.

Hope this helps,
Maarten
 
--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

http://www.maartenbuis.nl
--------------------------


      

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