Dear Statalist,
Is anyone aware of an article discussing (two-stage) selection
modeling in the context of multinomial/multivariate probit? I have a
selection indicator that is polytomous and would prefer to treat it as
multinomial when fitting the model. While -mvprobit- or -mprobit- can
be used to estimate the coefficients of the first-stage selection
equations, it is not clear to me how one would derive the inverse
Mills ratio (or its analog) or how this would enter into each of the
second-stage outcome equations.
I have scoured the literature and have found nothing relevant.
Cappellari and Jenkins have published on the use of multivariate
probit models to account for selectivity when the outcome is binary.
Also, I am aware of Stata's -selmlog- command and the related
literature. However, -selmlog- appears to require that the outcome be
missing for all save one of the selection categories. This is not the
case in my situation.
Thank you in advance.
Regards,
Jim
James W. Shaw, Ph.D., Pharm.D., M.P.H.
Assistant Professor
Department of Pharmacy Administration
College of Pharmacy
University of Illinois at Chicago
833 South Wood Street, M/C 871, Room 252
Chicago, IL 60612
Tel.: 312-355-5666
Fax: 312-996-0868
Mobile Tel.: 215-852-3045
*
* 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/
