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Re: st: OLS assumptions not met: transformation, gls, or glm as solutions?


From   Alan Acock <acock@me.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: OLS assumptions not met: transformation, gls, or glm as solutions?
Date   Thu, 20 Dec 2012 16:33:58 -0800

If I run 

regress qual_p conf_p i.sexrare ston_p forg_p sacr_p

were all variables but for sexrare are proportion of the maximum possible value, the interpretations are simple. A change in conf_p of one percentage point predicts a xx(coefficient) percentage point change in the outcome.

When I run

glm qual_p conf_p i.sexrare ston_p forg_p sacr_p, ///
 family(binomial) link(logit) vce(robust)

is there a clear interpretation of the coefficient or some transformation of the coefficients? 

I'm think the answer should be obvious to me, but it is not.

Alan Acock

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