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Re: st: RE: RE: problem running mfx after glm

From   Richard Williams <[email protected]>
To   [email protected]
Subject   Re: st: RE: RE: problem running mfx after glm
Date   Mon, 15 Aug 2011 19:25:00 -0500

At 06:04 PM 8/15/2011, Marlis Gonzalez Fernandez wrote:
I am trying to analyze a new variable (categorical 5 levels) still accounting for marginal effects since audcompCombdiv100 is a proportion so I wrote:

glm audcompCombdiv100 Age Gender0Male1Female DWIVolume i.Discharge_Location, family(binomial) link(logit) robust

mfx, at(mean)

-default predict() is unsuitable for marginal-effect calculation

Is the problem the use of -i.var-?

mfx doesn't like the i. notation. You could compute the dummies yourself, but mfx would not be smart enough to know that the dummies are all inter-related, e.g. if one dummy = 1 the others all have to equal 0. Use margins instead:

margins, dydx(*) atmeans

Also, my own bias would be to drop the -atmeans- option and use the default -asobserved- instead.

Richard Williams, Notre Dame Dept of Sociology
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