Bookmark and Share

Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Re: st: xtnbreg, nbreg, and tests of assumptions

From   "Mary E. Mackesy-Amiti" <[email protected]>
To   [email protected]
Subject   Re: st: xtnbreg, nbreg, and tests of assumptions
Date   Wed, 15 Dec 2010 11:03:07 -0600

I think you meant to say that your *dependent* variable is count with overdispersion, and your *independent* variable is time invariant. Independent variables predict dependent variables.

Please post the -xtnbreg- command you used and the results you find questionable.

On 12/15/2010 7:30 AM, Dalhia wrote:

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

Thanks so much. I really appreciate your help.

--- On Wed, 12/15/10, Maarten buis<[email protected]>  wrote:

From: Maarten buis<[email protected]>
Subject: Re: st: Difference between xtlogit, xtmelogit, gllamm
To: [email protected]
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 L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen

*   For searches and help try:

*   For searches and help try:

Mary Ellen Mackesy-Amiti, Ph.D.
Research Assistant Professor
Community Outreach Intervention Projects (COIP)
School of Public Health m/c 923
Division of Epidemiology and Biostatistics
University of Illinois at Chicago
ph. 312-355-4892
fax: 312-996-1450

*   For searches and help try:

© Copyright 1996–2018 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   Site index