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Re: st: OLS assumptions not met: transformation, gls, or glm as solutions? (Out of Office Autoreply: [email protected])
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Re: st: OLS assumptions not met: transformation, gls, or glm as solutions? (Out of Office Autoreply: [email protected])
Date
Fri, 21 Dec 2012 00:35:36 +0000
I am out of the office until Tuesday 8th January 2012. I shall deal with your enquiry upon my return. Enjoy the festive season!
Sarah Miller
Pathways Administrator
------------------------------------------------------
Department of Medical Statistics
London School of Hygiene & Tropical Medicine
Keppel Street
London
WC1E 7HT
http://pathways.lshtm.ac.uk
>>> Alan Acock <[email protected]> 12/21/12 00:33 >>>
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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