--- Irina Paley has trouble posting to statalist and asked
ma privately:
> Basically, I am running an mlogit for a choice between 4
> products, and when I don't include state dummies in the
> regression, mfx gives me statistically significant result
> for gender. But if I include state dummies in mlogit, mfx
> gives gender effect that is not stat sig. However, I also
> get this:
>
> run mlogit controlling for state, and set state dummies to
> 0 when asking for mfx: gender effect is stat sig, and
> similar to when I don't control for states in mlogit
> run mlogit controlling for state, and ask mfx for a
> specific state: gender effect is
> stat sig, and similar to when I don't contorl for states
> in mlogit
>
> probits also give stat sig effect of gender.
>
>
> why are results not stat sig when I ask for marginal
> effects after controlling for state? is it legitimate here
> to control for states in regressions but not include states
> in the mfx calculation? why does dprobit not have the same
> problem?
I don't think this is a problem. The marginal effect of any
variable in a non-linear model like -mlogit- or -probit-
depends on the values of all the covariates in the model, so
it could very well happen that the coefficient is significant
and the marginal effect of that variable is not significant
for some combinations of values for the covariates.
The key is to decide what combination of values makes sense
to you. If you include the variable in the -mlogit- model
but don't specify in -mfx- it will be set at the mean,
which I don't think makes sense.
Below I will give you a probably incomplete list of your
options, and at the bottom an example that implements these.
If you set all the dummies at zero you estimate the effect
of gender in the state you left out (the reference category),
which may or may not make sense.
If you can added the state dummies using effect coding and in
-mfx- set the state dummies to zero then you estimate the
effect of gender for the average state. You can include dummies
as effect coding using Michael Mitchell's and Phil Ender's -xi3-.
Type -findit xi3- to find it.
You can interpret the exponentiated coefficients as odds ratios.
These don't depend on the values of the other varialbes, which
greatly simplifies the interpretation. You can get thos by just
specifying the -rrr- option in -mlogit- (some people just like
to call these relative risk ratios, see here for my vies on it:
http://www.stata.com/statalist/archive/2007-02/msg00085.html .)
Yet another reasonable approach is to estimate the partional
effects for each individual and average these. This way you
get the average effect. You can do that with Tamas Bartus'
-margeff- package. Type -findit margeff- to find it.
In sum you are trying to summarize a non-linear relationship
with a single number. The odds ratios provide an exact
representation of the results of your model, but all other
approaches further simplify your model. As with any
simplification this requires a judgement call about which
simplification makes most sense in your particular situation.
*------------------ begin example ------------------------
sysuse auto, clear
egen prclass = cut(price), group(3)
recode rep78 1/2=3
xi3: mlogit rep78 i.prclass foreign
// this doesn't make sense
mfx, predict(pr eq(#1)) var(foreign)
// the effect of foreign in the lowest price class
mfx, predict(pr eq(#1)) ///
at(_Iprclass_1=0 _Iprclass_2=0 foreign =0) ///
var(foreign)
// the effect of foreign in the highest price class
mfx, predict(pr eq(#1)) ///
at(_Iprclass_1=0 _Iprclass_2=1 foreign =0) ///
var(foreign)
// the effect of foreign for an averagely priced car
xi3: mlogit rep78 e.prclass foreign
mfx, predict(pr eq(#1)) ///
at(_Iprclass_1=0 _Iprclass_2=0 foreign =0) ///
var(foreign)
// report the odds ratios
xi: mlogit rep78 i.prclass foreign, rrr
// averaged partial effects
margeff
*------------------ end example -----------------------
http://www.soziologie.uni-tuebingen.de/Institut/MitarbInst/Buis/Stata_examples_FAQ.html
Hope this helps,
Maarten
-----------------------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://www.soziologie.uni-tuebingen.de/Institut/MitarbInst/MBuis.html
-----------------------------------------
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