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Re: Re: st: Error w/ "inteff" command
From
Erasmo Giambona <[email protected]>
To
[email protected]
Subject
Re: Re: st: Error w/ "inteff" command
Date
Wed, 2 Jan 2013 19:34:51 +0100
Thanks Richard. I will read the documents carefully. I just skimmed
through the power point presentation for now. I think I got why there
is no marginal effect for the interaction term (for e.g., the
interaction of two dummy variables). But I need to uderstand this part
better. I always thought the marginal effect exists from the inteff
article.
Erasmo
On Wed, Jan 2, 2013 at 6:22 PM, Richard Williams
<[email protected]> wrote:
> I don't really understand how -inteff- works, nor do I have any great desire
> to find out. I am happy with the -margins- command, and the way you set it
> up is not correct for -margins-. When you compute the interaction term
> yourself, Stata has no way of knowing that the values of the interaction
> term are not independent of the values of the variables used to compute it.
> It should be
>
> webuse lbw2
> probit low age lwt c.age#c.lwt
> margins, dydx(_all)
>
> For an explanation, see
>
> http://www.nd.edu/~rwilliam/stats/Margins01.pdf
>
> or else
>
> http://www.statajournal.com/article.html?article=st0260
>
>
> At 10:48 AM 1/2/2013, Erasmo Giambona wrote:
>>
>> 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 <[email protected]>
>> 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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>> > * http://www.stata.com/help.cgi?search
>> > * http://www.stata.com/support/faqs/resources/statalist-faq/
>> > * http://www.ats.ucla.edu/stat/stata/
>>
>> *
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>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>> * http://www.ats.ucla.edu/stat/stata/
>
>
> -------------------------------------------
> Richard Williams, Notre Dame Dept of Sociology
> OFFICE: (574)631-6668, (574)631-6463
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>
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