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| From | brendan.halpin@ul.ie (Brendan Halpin) |
| To | statalist@hsphsun2.harvard.edu |
| Subject | Re: st: MIXLOGIT: marginal effects |
| Date | Thu, 09 Feb 2012 09:11:20 +0000 |
On Thu, Feb 09 2012, Nick Cox wrote: > I can't readily imagine many > situations in which I would prefer a linear probability model to a > logit model, but I still think it's too extreme. To play devil's advocate, let me mention Mood (2010), who argues that where unobserved heterogeneity makes it invalid to compare log-odds estimates sizes across samples, the LPM estimate can be more consistent. Brendan Mood (2010), 'Logistic Regression: Why We Cannot Do What We Think We Can Do, and What We Can Do About It', European Sociological Review, Volume 26, Issue 1 Pp. 67-82. -- Brendan Halpin, Department of Sociology, University of Limerick, Ireland Tel: w +353-61-213147 f +353-61-202569 h +353-61-338562; Room F1-009 x 3147 mailto:brendan.halpin@ul.ie ULSociology on Facebook: http://on.fb.me/fjIK9t http://teaching.sociology.ul.ie/bhalpin/wordpress twitter:@ULSociology * * 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/