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RE: st: biprobit predict command
From
"Garrido, Melissa" <[email protected]>
To
"'[email protected]'" <[email protected]>
Subject
RE: st: biprobit predict command
Date
Thu, 26 May 2011 14:26:15 +0000
Hi Jean-Christophe,
One thing to consider with your first question is the issue of interpretability. What does a prediction based on the mean of a binary variable represent? For example, if your binary variable was whether someone was married, you'd be estimating the effect of hybrid individuals who were/were not married. Depending on how many binary IVs you have, it may be worth considering holding individual IVs constant at 0 or 1 and then getting the predictions.
I'm not sure how to answer your second question; hopefully someone else has an answer for you.
- Melissa
>From Jean-Christophe Boucher <[email protected]>
>To "[email protected]" <[email protected]>
>Subject st: biprobit predict command
>Date Wed, 25 May 2011 16:21:30 -0400
>Hi,
>I am using a bivariate probit model with partial observability (biprobit)
>where some of the IVs in the first equation are either binary or continuous.
>Right now I have used the adjust stata command in order to predict
>estimations of the continuous IVs while keeping all other IVs at their
>means. There are two issues that worries me:
>1) Is keeping binary IVs at their means to estimate predictions is worrisome
>2) In bivariate models, the prediction commands only works for the first
>equations, should I be worried about not accounting for the rho in the
>prediction? Or is it already included in the biprobit results? Is there any
>specific command to use post-estimation technics for multilevel model such
>as the one I am using?
>JC
--------------------------------------------------------------------
Melissa Garrido, PhD
Research Health Science Specialist
GRECC/REAP, James J Peters VA Medical Center
130 West Kingsbridge Road
Bronx, NY 10468
718-584-9000 x 3804
[email protected]
Assistant Professor
Brookdale Department of Geriatrics & Palliative Medicine
Box 1070
Mount Sinai School of Medicine
One Gustave L. Levy Place
New York, NY 10029
[email protected]
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