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RE: st: Obtaining marginal effects and their standard errors after estimations with interactions


From   Ebru Ozturk <ebru_0512@hotmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Obtaining marginal effects and their standard errors after estimations with interactions
Date   Fri, 4 Jan 2013 19:24:52 +0200

It's not that hard, just you need to be careful. Stata 10 is the only choice for me. I just need an example that inludes a few more independent and control variables.

Ebru

----------------------------------------
> From: richardwilliams.ndu@gmail.com
> Date: Fri, 4 Jan 2013 11:56:50 -0500
> Subject: Re: st: Obtaining marginal effects and their standard errors after estimations with interactions
> To: statalist@hsphsun2.harvard.edu
>
> I hate trying to do something like this by hand. Too much room for
> error. Can't you tell whoever you work for that you can't be expected
> to work under such primitive inhumane conditions and you need Stata
> 12?
>
> You might check out the user-written -inteff- command and see if it
> helps. -margeff- is another user-written command that has various
> advantages over -mfx-.
>
> Sent from my iPad
>
> On Jan 4, 2013, at 11:33 AM, Ebru Ozturk <ebru_0512@hotmail.com> wrote:
>
> > Thank you, I use Stata 10 therefore I asked this question. I just wonder when we have more independent or control variables how do we adjust the given equations on this link: http://www.stata.com/support/faqs/statistics/marginal-effects-after-interactions/
> >
> > Kind regards
> > Ebru
> >
> > ----------------------------------------
> >> Date: Fri, 4 Jan 2013 09:32:25 -0500
> >> To: statalist@hsphsun2.harvard.edu; statalist@hsphsun2.harvard.edu
> >> From: richardwilliams.ndu@gmail.com
> >> Subject: Re: st: Obtaining marginal effects and their standard errors after estimations with interactions
> >>
> >> At 03:17 PM 1/3/2013, Ebru Ozturk wrote:
> >>
> >>> Dear All,
> >>>
> >>> On Stata FAQs' page, there are some given examples for Probit
> >>> estimation with interaction effects for Stata 10 titled as "I am
> >>> using a model with interactions. How can I obtain marginal effects
> >>> and their standard errors?" and the link is:
> >>> http://www.stata.com/support/faqs/statistics/marginal-effects-after-interactions/
> >>>
> >>> Do you think this way is still applicable to Probit estimation? and
> >>> Is the below command correct when we have other independent or
> >>> control variables?
> >>
> >> I don't know if you did it right or not, but if you have Stata 11 or
> >> higher why not use -margins-, e.g.
> >>
> >> sysuse auto, clear
> >> probit foreign weight length c.weight#c.length, nolog
> >> margins, dydx(*)
> >>
> >>> local xb _b[weight]*`meanwei' + _b[len]*`meanlen' +
> >>> _b[wl]*`meanwei'*`meanlen' + _b[C1]*C1+_b[C2]*C2 + _b[_cons] // if
> >>> more variables //
> >>>
> >>> /////// example /////////
> >>>
> >>> sysuse auto, clear
> >>> generate wl=weight*length
> >>> probit foreign weight length wl, nolog
> >>> quietly summarize weight if e(sample)
> >>> local meanwei = r(mean)
> >>> quietly summarize length if e(sample)
> >>> local meanlen = r(mean)
> >>>
> >>> local xb _b[weight]*`meanwei' + _b[len]*`meanlen' +
> >>> _b[wl]*`meanwei'*`meanlen' + _b[_cons]
> >>> predictnl dydw = normalden(`xb')*(_b[weight]+ _b[wl]*`meanlen') in 1, se(sew)
> >>> list dydw sew in 1
> >>>
> >>> predictnl dydl = normalden(`xb')*(_b[len]+ _b[wl]*`meanwei') in 1, se(sel)
> >>> list dydl sel in 1
> >>>
> >>> predictnl dydlw =normalden(`xb')*(-(`xb'))*(_b[weight]+
> >>> _b[wl]*`meanlen')*(_b[len]+ _b[wl]*`meanwei') + normalden(`xb')*(
> >>> _b[wl]) in 1, se(selw)
> >>> list dydlw selw in 1
> >>>
> >>> Ebru
> >>
> >> -------------------------------------------
> >> Richard Williams, Notre Dame Dept of Sociology
> >> OFFICE: (574)631-6668, (574)631-6463
> >> HOME: (574)289-5227
> >> EMAIL: Richard.A.Williams.5@ND.Edu
> >> WWW: http://www.nd.edu/~rwilliam
> >>
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