Statalist


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

Re: st: problem of running xtlogit, fe


From   "J. Li" <lij53@univmail.cis.mcmaster.ca>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: problem of running xtlogit, fe
Date   Mon, 26 Oct 2009 17:39:17 -0400

Maarten,

Thanks for the information you gave. I think you are right-- there is
no within-individual variation for a big proportion of the sample I
used. Can I ask though why the the note says that "multiple positive
outcomes within groups encountered"? If the problem is that there is no
within-group variation, why are there multiple positive outcomes within
groups? I checked the outcome variable, it is only valued as 0 or 1 so
I don't understand what this notes really means. Also, I have
encountered another notes saying "1,066 individuals dropped due to all
positive or all negative outcomes." when I was trying the same program
with another sample. Is this essentially the same problem happening
again? Thanks a lot!

Daisy


On Thu, 8 Oct 2009 05:56:10 +0000 (GMT)
 Maarten buis <maartenbuis@yahoo.co.uk> wrote:
> 
> 
> --- On Thu, 8/10/09, J. Li <lij53@univmail.cis.mcmaster.ca> wrote:
> > I am now running a fixed effect logit model using the
> > following lines.
> > (Note that the panel data I am using is with N=2,200 and
> > T=10.) 
> > 
> > iis id
> > xtlogit status treatment age group, i(id) fe 
> > mfx, predict(pu0)
> > 
> > STATA then gave the notes as following--
> > 
> > note: multiple positive outcomes within groups
> > encountered.
> > note: 2054 groups (20506 obs) dropped due to all positive
> > or
> >       all negative outcomes.
> > 
> > After that STATA ran over more than 3000 iterations without
> > stopping nor giving any results. The log-likelihood values
> > didn't improve after iteration 40. For each iteration, it
> > showed  "(not concave)" after every log likelihood value.
> > Do you know why is this happening?
> 
> Fixed effects regression uses only information from changes within
> an individual (firm, country, or whatever your unit may be), it
> throws away all information that could be obtained from comparing
> individuals. So, a fixed effects regression can do nothing with an
> individual that doesn't change over time, and such an individual
> is removed. Apparently, your data mainly consists of individuals
> who do not change over time (as 2054 of your 2200 individuals where
> dropped). Which means there is only a very small sample left. I 
> would check whether this is correct, e.g. make sure that your 
> dependent variable is coded 0, 1 and not 1, 2. If it is true that 
> there is very little variation in outcome within individuals then
> your problem is just not suitable for being analyzed with fixed
> effects regression, and you can move on to random effects regression.
> 
> Hope this helps,
> Maarten
>  
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
> 
> http://www.maartenbuis.nl
> --------------------------
> 
> 
> 
>       
> 
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/



© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index