Stata The Stata listserver
[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

Re: st: xtgee vs xtlogit

Subject   Re: st: xtgee vs xtlogit
Date   Sun, 3 Nov 2002 15:06:54 -0500 (EST)

This is exactly the information I was looking for.  Thank you!

---- Original message ----
>Date: Sat, 02 Nov 2002 23:01:47 +0900
>From: Joseph Coveney <>  
>Subject: Re: st: xtgee vs xtlogit  
>Marie Olson posted a general question about the use of
-xtgee- and 
>---------begin excerpted post---------
>Can anyone tell me why I might choose xtgee over xtlogit when 
>analyzing a dataset  of 30 countries for a period of 41
years? My 
>variables are the following:
>dep v:  war/no war
>indeps:  policy/no policy, regime score, gdp change, peace years
>The hypothesis is that certain types of policies are
associated with 
>the occurrence of  violence, controlling for regime score, gdp 
>fluctuations, and the number of peace  years prior to the
>---------end excerpted post---------
>Gary King ( has looked into 
>statistical models for relatively rare events in similar
kinds of 
>surveys, and has made ReLogit available for Stata.
>As to Marie's question, I'm no expert, but -xtgee- (or
-xtlogit, pa-) 
>would seem to  have certain advantages, such as the ability
to use 
>autoregressive working  correlation structures.  With 41
years of 
>data, such correlations might be apparent.  Parameter estimates 
>(regression coefficients) and parameter standard errors from 
>population-average generalized estimating equation (PA-GEE) 
>approach, as implemented in -xtgee, robust-, are relatively
>to misspecification of the working correlation structure.
>On the other hand, PA-GEE works best with lots of panels; with 
>only 30 nations, the panel number might not be sufficient to
give a 
>lot of confidence in hypothesis testing results from -xtgee-.
>addition, I was led to beleive that PA-GEE isn't so great
with long 
>panels--somewhere I had read that panel lengths of around six or 
>fewer are ideal.  A good source for advice is the user's manual.
>If she believes that there is important autocorrelation, it
might be 
>worth considering grouping the 41-year span into epochs of
>lengths of time and use -xtgls- on the proportion (or arcsin-
>transformed proportion) of time at-war in each successive
>With blocking the time span into epochs, -xtgee- and
-xtlogit- would 
>have fewer intervals to cope with, and might be better behaved.  
>For these epochs, alternative approaches could be considered, 
>such as Poisson regression (or zero-inflated Poisson regression, 
>hopefully) for the number of wars or years at war in successive 
>I have a concern about using number of years at peace as a 
>predictor in Marie's statistical model of her data.  It would
seem that 
>such a predictor and the response variable would be confounded --
>years at peace is implied in a war/no-war dependent variable
in a 
>longitudinal survey.  Last month, Wiji Arulampalam posted to the 
>list about having difficulty getting proper convergence with -
>xtprobit- and she wondered whether it might have to do with the 
>presence of a time-lagged variable in the list of predictors
in her 
>case.  It seems that an analogous situation arises in Marie's
>Perhaps the use of an autocorrelation structure will obviate the 
>need for years at peace as a predictor.
>Joseph Coveney
>*   For searches and help try:

*   For searches and help try:

© Copyright 1996–2017 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index