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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 |
Mon, 7 Jan 2013 19:00:12 +0200 |

Thank you very much, it helped a lot :) ---------------------------------------- > Date: Mon, 7 Jan 2013 15:08:18 +0000 > Subject: Re: st: Obtaining marginal effects and their standard errors after estimations with interactions > From: arnehole@gmail.com > To: statalist@hsphsun2.harvard.edu > > It's possible to get pretty close when both variables are continuous > as well, using a finite difference approximation. The code below > approximates "dydlw" in the FAQ. > > sysuse auto, clear > replace weight=weight/1000 > replace length=length/10 > probit foreign weight length c.weight#c.length, nolog > margins, dydx(*) atmeans at(weight=3.019559) > matrix b = r(b) > scalar meff_turn_1 = b[1,2] > margins, dydx(*) atmeans at(weight=3.019459) > matrix b = r(b) > scalar meff_turn_0 = b[1,2] > > di (meff_turn_1 - meff_turn_0)/0.0001 > > I'm not saying that this is a good way of actually performing these > calculations, but it does help in giving some intuition to what the > numbers represent (at least I think so). > > Arne > > On 7 January 2013 13:41, Arne Risa Hole <arnehole@gmail.com> wrote: > > I don't have much to add to what Richard has already said on this > > topic but I just wanted to mention one thing: if the interaction is > > between a continuous variable and a dummy variable, then the second > > derivative (or "marginal effect of the interaction") is the difference > > between the marginal effect of the continuous variable when the dummy > > is "switched on" and when dummy is "switched off". The code below > > replicates the final result in the FAQ (this uses -margins- so > > requires Stata 11 or higher). > > > > sysuse auto, clear > > set seed 12345 > > generate dum=uniform()>0.5 > > table dum > > probit foreign turn i.dum i.dum#c.turn, nolog > > > > margins, dydx(*) atmeans at(dum=1) > > matrix b = r(b) > > scalar meff_turn_dum1 = b[1,1] > > margins, dydx(*) atmeans at(dum=0) > > matrix b = r(b) > > scalar meff_turn_dum0 = b[1,1] > > > > di meff_turn_dum1 - meff_turn_dum0 > > > > Arne > > > > On 6 January 2013 13:11, Ebru Ozturk <ebru_0512@hotmail.com> wrote: > >> But without getting separate interaction terms, how do we know that the moderator affects the relationship between x and y positively or negatively? > >> > >> ---------------------------------------- > >>> Date: Sat, 5 Jan 2013 13:39:53 -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 > >>> > >>> Thanks for the references. FYI, if you have Stata > >>> 11 or higher, here is how you can easily > >>> reproduce almost everything that is in the FAQ at > >>> http://www.stata.com/support/faqs/statistics/marginal-effects-after-interactions/ > >>> -- the one exception being that you DON'T get > >>> separate marginal effects for the interaction terms. > >>> > >>> sysuse auto, clear > >>> regress mpg weight c.weight#c.weight > >>> margins, dydx(*) atmeans > >>> sysuse auto, clear > >>> replace weight=weight/1000 > >>> replace length=length/10 > >>> probit foreign weight length c.weight#c.length, nolog > >>> margins, dydx(*) atmeans > >>> sysuse auto, clear > >>> set seed 12345 > >>> generate dum=uniform()>0.5 > >>> table dum > >>> probit foreign turn i.dum i.dum#c.turn, nolog > >>> margins, dydx(*) atmeans > >>> > >>> With regards to the references, Greene is > >>> brilliant but I wish he would write in English > >>> and use Stata examples. I think he is saying that > >>> the marginal effect of the interaction is not > >>> useful. The other two articles are also > >>> expressing concerns or suggesting alternatives. I > >>> am also not a big fan of using MEMs (marginal > >>> effects at the means); AMEs (Average Marginal > >>> Effects) make more sense to me, especially when > >>> categorical variables are involved. > >>> > >>> If the marginal effect of the interaction term is > >>> useful or even valid, I continue to wonder why > >>> -margins- does not provide it. And what exactly > >>> does it mean? The interaction term can't change > >>> independently of the variables used to compute the interaction. > >>> > >>> At 11:53 AM 1/5/2013, AndrÃ© Ferreira Coelho wrote: > >>> >Dear all, > >>> > > >>> >As far as i know there is no consensus on whether margins should be > >>> >computed for marginal terms. > >>> > > >>> >Maybe you are interested in using odds for interactions instead of > >>> >margins. > >>> > > >>> >But you might want to take a look on some literature: > >>> > > >>> >http://www.maartenbuis.nl/publications/interactions.pdf > >>> > > >>> >http://pages.stern.nyu.edu/~wgreene/DiscreteChoice/Readings/Greene-Chapter-23.pdf > >>> > > >>> >http://www.stata-journal.com/sjpdf.html?articlenum=st0063 > >>> > > >>> >Best, > >>> > > >>> >Andre > >>> > > >>> > > >>> > > >>> > > From: ebru_0512@hotmail.com > >>> > > To: statalist@hsphsun2.harvard.edu > >>> > > Subject: RE: st: Obtaining marginal effects and their standard errors > >>> >after estimations with interactions > >>> > > Date: Sat, 5 Jan 2013 13:32:47 +0200 > >>> > > > >>> > > Yes,that's true but I dont think it is wrong to produce a separate > >>> >marginal > >>> >effect. Also this 2004 FAQ is for Stata 10. Maybe that's the reason to > >>> >still have this information on FAQ page. > >>> > > >>> >---------------------------------------- > >>> > > Date: Fri, 4 Jan 2013 15:15:58 -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 12:24 PM 1/4/2013, Ebru Ozturk wrote: > >>> > > >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 > >>> > > > >>> > > I think it is interesting that the -margins- command works somewhat > >>> > > differently than the approach presented in the FAQ. In particular, > >>> > > margins does not produce a separate marginal effect for the > >>> > > interaction term while the FAQ approach does. This makes me wonder if > >>> > > (a) the 2004 FAQ is now considered wrong, or (b) both the FAQ and > >>> > > margins approaches are considered legitimate but alternative > >>> > > approaches. Personally, I think what margins does is very logical, > >>> > > but nonetheless people keep on asking for marginal effects of > >>> > > interaction terms. > >>> > > > >>> > > >---------------------------------------- > >>> > > > > 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 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/ > >>> >[1] > >>> > > > > > > >>> > > > > > 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/ > >>> >[2] > >>> > > > > >>> > >>> > > > > >>> 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 > >>> > >>> > >>> * > >>> * For searches and help try: > >>> * http://www.stata.com/help.cgi?search > >>> * http://www.stata.com/support/faqs/resources/statalist-faq/ > >>> * http://www.ats.ucla.edu/stat/stata/ > >> * > >> * For searches and help try: > >> * http://www.stata.com/help.cgi?search > >> * http://www.stata.com/support/faqs/resources/statalist-faq/ > >> * http://www.ats.ucla.edu/stat/stata/ > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**RE: st: Obtaining marginal effects and their standard errors after estimations with interactions***From:*André Ferreira Coelho <andre.f.coelho2011@novasbe.pt>

**RE: st: Obtaining marginal effects and their standard errors after estimations with interactions***From:*Richard Williams <richardwilliams.ndu@gmail.com>

**RE: st: Obtaining marginal effects and their standard errors after estimations with interactions***From:*Ebru Ozturk <ebru_0512@hotmail.com>

**Re: st: Obtaining marginal effects and their standard errors after estimations with interactions***From:*Arne Risa Hole <arnehole@gmail.com>

**Re: st: Obtaining marginal effects and their standard errors after estimations with interactions***From:*Arne Risa Hole <arnehole@gmail.com>

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