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From |
Erasmo Giambona <e.giambona@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: Re: st: Error w/ "inteff" command |

Date |
Tue, 8 Jan 2013 18:36:55 +0100 |

Dear Richard, I have read your Stata's article carefully and I think I understand better why marginal effects on interaction terms (e.g., interactio of two dummy variables) do not exist in the case of non-linear models. But what about Linear Probability Models? Can I simply use the slope coefficient on the interaction term in this case to measure the marginal effect? I would appreciate you answer on this issue. Best regards, Erasmo > On Wed, Jan 2, 2013 at 6:22 PM, Richard Williams > <richardwilliams.ndu@gmail.com> 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 <kit.baum@bc.edu> >>> 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 >>> > >>> > >>> > * >>> > * 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/ >> >> >> ------------------------------------------- >> 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/

**References**:**Re: Re: st: Error w/ "inteff" command***From:*Erasmo Giambona <e.giambona@gmail.com>

**Re: Re: st: Error w/ "inteff" command***From:*Richard Williams <richardwilliams.ndu@gmail.com>

**Re: Re: st: Error w/ "inteff" command***From:*Erasmo Giambona <e.giambona@gmail.com>

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