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Re: st: triprobit convergence problem


From   Antoine Terracol <Antoine.Terracol@univ-paris1.fr>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: triprobit convergence problem
Date   Mon, 22 Mar 2010 11:33:30 +0100

Also, as the author of -triprobit-, I would advise Roy to give -mvprobit- a try. -mvprobit- uses more efficient code than my -triprobit- (and is also faster); that might solve Roy's convergence problems.

Antoine

Maarten buis <maartenbuis@yahoo.co.uk> a écrit :

--- 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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