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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 |
Sun, 6 Jan 2013 15:11:18 +0200 |

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/

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

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