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Re: st: triprobit convergence problem
From
Maarten buis <[email protected]>
To
[email protected]
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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