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# Re: Re: st: Error w/ "inteff" command

 From Erasmo Giambona To statalist@hsphsun2.harvard.edu Subject Re: Re: st: Error w/ "inteff" command Date Wed, 2 Jan 2013 16:48:45 +0100

```Dear Kit,

I was finally able to get the "inteff" command to work again. Inteff
and margins give me estimates on the interaction term that are
similar, but not the same. Is this simply do to different
approximation? Thanks. Please, see example below (using: webuse lbw2):

. g age_lwt=age*lwt

. probit  low age lwt age_lwt

Iteration 0:   log likelihood =   -117.336
Iteration 1:   log likelihood = -113.61015
Iteration 2:   log likelihood = -113.58509
Iteration 3:   log likelihood = -113.58509

Probit regression                                 Number of obs   =        189
LR chi2(3)      =       7.50
Prob > chi2     =     0.0575
Log likelihood = -113.58509                       Pseudo R2       =     0.0320

------------------------------------------------------------------------------
low |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
age |  -.0316919   .0896229    -0.35   0.724    -.2073495    .1439658
lwt |  -.0087146   .0162868    -0.54   0.593     -.040636    .0232069
age_lwt |   .0000561   .0006749     0.08   0.934    -.0012666    .0013788
_cons |   1.186736   2.124989     0.56   0.577    -2.978165    5.351637
------------------------------------------------------------------------------

. inteff low age lwt age_lwt
Probit with two continuous variables interacted
(0 observations deleted)

Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
_probit_ie |       189    .0000473    7.14e-06   .0000265   .0000548
_probit_se |       189    .0002247    .0000631   .0000304   .0002841
_probit_z |       189    .2615582    .2009778   .1001468   1.322986

. margins, dydx(_all)

Average marginal effects                          Number of obs   =        189
Model VCE    : OIM

Expression   : Pr(low), predict()
dy/dx w.r.t. : age lwt age_lwt

------------------------------------------------------------------------------
|            Delta-method
|      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
age |  -.0108404   .0306064    -0.35   0.723    -.0708278    .0491469
lwt |  -.0029809   .0055547    -0.54   0.592    -.0138679    .0079061
age_lwt |   .0000192   .0002308     0.08   0.934    -.0004332    .0004715
------------------------------------------------------------------------------

On Sat, Dec 29, 2012 at 11:16 PM, Christopher Baum <kit.baum@bc.edu> wrote:
> <>
> Erasmo said
>
> Does - margins, dydx(_all) - also handle the interaction of two dummy variables?
>
> Yes. ht (hypertension, yes/no) and smoke (yes/no) are such, and interacted in the model below. Notice that each has a positive main effect on low bw, but if they appear together the effect is, strangely enough, reduced (although the negative interaction coefficient is not distinguishable from zero).
>
> probit low c.age##i.race i.ht##i.smoke
> margins, dydx(_all)
>
>
>
> Kit Baum   |   Boston College Economics & DIW Berlin   |   http://ideas.repec.org/e/pba1.html
>                              An Introduction to Stata Programming  |   http://www.stata-press.com/books/isp.html
>   An Introduction to Modern Econometrics Using Stata  |   http://www.stata-press.com/books/imeus.html
>
>
> *
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```