Re: st: problem with Margin command and interaction graph in fixed effect logistic regression

[Klaus Pforr <kpforr@googlemail.com>]

<>

Dear Nahla,

margins basically evaluates the function outcome|indep. vars for 
specific values for the indep. var's. With the dydx-option, you get 
discrete or marginal changes of this function, which means that this 
evaluates differences of the abovementioned function, where for 
continouos variables the differences are infinitesimal small and for 
discrete variables they are unit-steps (unless you specify other options).

Note however that with the clogit command you generally have the 
problem, that the function for the outcome-prob dependent on the indep. 
var's is not completely specified, as the unobserved term alpha is not 
estimated. If you use clogit to estimate fixed-effects-logit-models, 
there is no easy way out. You can only estimate effects on the logit or 
the odds-ratio, i.e. the index-function or propensity for an 
alternative. If you use clogit to estimate a mcfadden-choice-model, the 
unobserved component is determined by the number of alternatives (unless 
you have the situation of more than one choice out of many 
alternatives). In the mc-fadden-choice-model case, you can specify a 
value for alpha, and estimate predicted probabilities. This follows from 
the equivalence of this model to mlogit. This type of model is 
implemented for straightforward use with asclogit.

So to repeat, it depends on your model, how to use margins and interpret 
the estimates from clogit, and it is easier to use one of the two models 
to come to the right form of interpretation.

best regards

Klaus

Am 01.11.2013 16:31, schrieb Nahla Betelmal:
> Thank you both Alfonso and Klaus for the great help.
>
> I run the following command for each interaction, all worked fine.
>
> margins DV, predict(pu0) at( IVA=(-1.5(0.5)1.5))
>
> margins DV, predict(pu0) at( IVB=(-1.5(0.5)1.5))
>
> margins DV, predict(pu0) at( IVC=(-1.5(0.5)1.5))
>
> I did not use dydx as I did not fully understand it
>
> Thank you so much
>
> Nahla
>
> On 31 October 2013 18:57, Alfonso Sánchez-Peñalver
> <alfonso.statalist@gmail.com> wrote:
> > Hi Nahla,
> >
> > I’ve digged a little more into this. First, I found this in the archive using clogit and margins:
> >
> > http://www.stata.com/statalist/archive/2010-08/msg01454.html
> >
> > It seem that you have to specify the dydx() and predict options to have it work. To illustrate, the following two examples work
> >
> > ——————————— Begin Code ——————————————
> > webuse lowbirth2, clear
> > clogit low lwt smoke ptd ht ui i.race, group(pairid)
> > margins race, dydx(lwt) predict(pu0) at(lwt=(100(10)200))
> > ——————————— End Code ———————————————
> >
> > However, the following does not
> >
> > ——————————— Begin Code ——————————————
> > webuse lowbirth2, clear
> > clogit low c.lwt##i.smoke ptd ht ui i.race, group(pairid)
> > margins race, dydx(lwt) predict(pu0) at(lwt=(100(10)200))
> > ——————————— End Code ———————————————
> >
> > The problem is that it predicts the marginal effects when the fixed effects are zero. I hope this sheds some light.
> >
> > Alfonso
> >
> > On Oct 31, 2013, at 12:51 PM, Nahla Betelmal <nahlaib@gmail.com> wrote:
> >
> > > > margins drug, at(studytime=(10(5)30))
> >
> > *
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--
__________________________________
Dr. Klaus Pforr
GESIS -- Leibniz Institut für Sozialwissenschaft
B2,1
Postfach 122155
D - 68072 Mannheim
Tel: +49 621 1246 298
Fax: +49 621 1246 100
E-Mail: klaus.pforr@gesis.org
__________________________________

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