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From |
Arne Risa Hole <arnehole@gmail.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 15:08:18 +0000 |

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/

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

**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>

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