Re: st: logit average "marginal" effect of dummy variable with predict

[Richard Williams <richardwilliams.ndu@gmail.com>]

You are treating smoke as a continuous variable rather than as 
discrete. Instead do

logit low lwt ptd i.smoke age
margins, dydx(smoke) //AME of smoke

The latter produces

Average marginal effects                          Number of obs   =        112
Model VCE    : OIM

Expression   : Pr(low), predict()
dy/dx w.r.t. : 1.smoke

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     1.smoke |    .229702   .0923031     2.49   0.013     .0487913    .4106127
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.


Incidentally, I like this alternate syntax, mostly because of the way 
output gets labeled, especially in graphs:

margins r.smoke

At 07:48 AM 5/7/2013, Chris wrote:
> Dear statalist,
>
> I want to compute the average marginal effect of an interaction
> effect, so I have to simultaneously "switch on and off" two treatment
> dummies (one treatment dummy, and one subgroup dummy interacted with
> the treatment dummy). Margins can't do that, as Richard Williams
> recently pointed out here on statalist.
> (http://www.stata.com/statalist/archive/2013-01/msg00263.html)
>
> So I am trying to compute it manually. However, I don't even manage to
> compute the average marginal effect with the predict command; somehow,
> there is a discrepancy between margins and predict even for simple
> cases. Does anybody know why? Example:
>
> -------------------------------
> webuse lowbirth, clear
> logit low lwt ptd smoke age
> margins, dydx(smoke) //AME of smoke
>
> replace smoke=1 //set entire sample smoke=1
> predict withsmoke //predict probability
> replace smoke=0 //set entire sample smoke=0
> predict withoutsmoke //predict probability
> gen me=withsmoke-withoutsmoke //compute discrete "marginal" effect
> egen ame=mean(me) //AME of smoke
> -------------------------------
>
> The margins command gives an AME of .2198375, while the predict
> version gives .2297. Which is right and why do they differ?
>
> Thanks!
> *
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-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
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EMAIL:  Richard.A.Williams.5@ND.Edu
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