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| From | "Rourke O'Brien" <rourke.obrien@gmail.com> |
| To | statalist@hsphsun2.harvard.edu |
| Subject | st: oglm and heterogeneous choice models |
| Date | Sat, 23 Jul 2011 16:33:54 -0400 |
I am currently running logit models predicting success (dichotomous) with sex and income as main predictors. I understand that with potential unequal variances across groups I should explore heterogeneous choice models. See: http://www.nd.edu/~rwilliam/oglm/RW_Hetero_Choice.pdf when I run --oglm success male income, het(male)-- the lnsigma on male is significant. Yet, when I include the interaction (which is my main interest) ---oglm male income maleXincome, het(male)-- lnsigma is no longer significant. How should I interpret this? Does this mean that the inclusion of the interaction effectively modeled the source of the unequal variances across groups? If so, do I need to use oglm on models that include the interaction? Thanks for your help! * * 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/