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Re: st: triprobit convergence problem


From   Maarten buis <maartenbuis@yahoo.co.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: triprobit convergence problem
Date   Mon, 22 Mar 2010 02:41:57 -0700 (PDT)

--- On Sun, 21/3/10, Roy, Manan wrote:
> I am trying to estimate triprobit models with different
> time categories (as dummies) and 2 binary program
> participation variables.
> 
>  I have 2 almost identical data sets, one with N=1600 and
> the other with N=1000.
> There are 2 time categories for which the models are not
> converging. Let's call them TIME1 and TIME2.=20
> TIME1 converges in N=1600 data while it doesn't in N=1000
> data. The exactly opposite case holds for TIME2.

1000 and 1600 seems to me a bit small for this type of model, 
especially when your subdividing that small sample size in
smaller bits. A solution would be to stack those datasets, 
add dummies for dataset and periods and interactions. But
instead of adding all dummies + interactions impose some 
reasonable constraints (leave some interactions out, saying
that the effects of those variables are the same across 
datasets, or replace time dummies with a linear trend or
a spline, etc.) These kinds of constraints allow you to
use more information from similar groups to estimate the 
parameters, which means the model is more likely to converge.

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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