--- On Thu, 4/2/10, Jitian Sheu wrote:
> I am running a very very simple binary model, y=a+bX+e,
> where y is a dummy variable.
> Before performing -logit- command, I estimate the above
> model by a traditional OLS, i.e. linear probability model
> (regress y x1 x2...)
>
> I knew that OLS is not a good model for fitting this model.
> I just want to get some direction from results obtained
> from traditional OLS
>
> However, after I perform -regress- and -logit-, I found
> signs of estimated coefficients from these two models are
> not the same.
>
> I am just wondering whether this is "normal"? or I am doing
> anything wrong?
This is not normal. One possiblity I could imagine is that
you specified the -or- option (or used -logistic-) and
forgot to interpret coefficients less than 1 as negative
effects. In both case you will get odds ratios, that is, the
ratio by which the odds of "success" on y changes for a
unit change in x. An odds ratio less than 1 thus means
that a unit increase in x leads to a smaller odds, i.e.
a negative effect, even though the numberical value of the
odds ratio is positive. I wrote a small text about odds, odds
ratios, and marginal effects (in the context of interaction
effects), which is available here: <http://www.maartenbuis.nl/
wp/interactions.html>
Hope this helps,
Maarten
--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://www.maartenbuis.nl
--------------------------
*
* 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/
