<>
Just try to find it out with the examples in the help file. But you are
probably more interested in marginal effects than the coefficients
themselves?
*************
webuse lbw, clear
glm low age lwt i.race smoke ptl ht ui, family(gaussian) link(identity)
margins, dydx(*)
glm low age lwt i.race smoke ptl ht ui, family(binomial 1) link(logit)
margins, dydx(*)
*************
HTH
Martin
-----Ursprüngliche Nachricht-----
Von: [email protected]
[mailto:[email protected]] Im Auftrag von Jitian Sheu
Gesendet: Donnerstag, 4. Februar 2010 16:02
An: [email protected]
Betreff: st: Why do logit model coefficients produce signs opposite to those
obtained from OLS?
Dear listers:
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?
Many thanks.
Jitian
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