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From |
Lisa Marie Yarnell <lisayarnell@yahoo.com> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>, "alessandro.freire@gmail.com" <alessandro.freire@gmail.com> |

Subject |
Re: st: What is the effect of centering on marginal effects? |

Date |
Wed, 1 Aug 2012 09:56:48 -0700 (PDT) |

Thanks, Alessandro. Centering reduces collinearity between the centered variable and an interaction term created by cross-multiplying it with another centered variable, though, right? Yes, we had seen the "margins" command used before in the context of obtaining marginal effects for the selection equation in the heckman model. I am still a little unclear why centering the variable would not change the beta estimated in the model, but would change the marginal effect (what we saw). Any other guidance is appreciated. Thanks, Lisa ----- Original Message ----- From: Alessandro Freire <alessandro.freire@gmail.com> To: statalist@hsphsun2.harvard.edu Cc: Sent: Wednesday, August 1, 2012 6:54 AM Subject: Re: st: What is the effect of centering on marginal effects? Dear Lisa, Centered and uncentered models are algebraically equivalent (see Brambor et al, "Understanding Interaction Models: Improving Empirical Analyses" 2006). The only difference is that, in an uncentered model, the coefficient of b1 corresponds to the marginal effect of a one unit change in X when the conditioning variable Z is zero, while the corresponding coefficient on the centered model gives you the marginal effect of a change in X when Z is at its mean. This means that centering variables will not reduce multicollinearity on your model. I am not familiar with the mfx command, but I would suggest you to either perform the estimation of marginal effects by hand (see https://files.nyu.edu/mrg217/public/interaction.html) or use the margins command, which supports factor variables, if you are using Stata 11. I hope this helps. Best wishes, Alessandro Freire On Tue, Jul 31, 2012 at 11:53 PM, Lisa Marie Yarnell <lisayarnell@yahoo.com> wrote: > > Hi Stata users, > > What is the effect of centering one's predictors on marginal effects? We centered our variables prior to cross-multiplication in the creation of interaction terms to avoid multicollinearity. We found that centering did not change the effect of the beta in our heckman model, but it eliminated the marginal effects produced by a mfx dyex command. Why would that be? > > I don't think it's due to Stata estimating the marginal effects "at" another value because Stata estimates marginal effects at the mean by default, and the mean of the uncentered variable at hand (M = .29) is the equivalent of the mean of the centered variable (M = .00) because in centering the variable, we subtracted .29 from all scores. > > Thanks, > Lisa > > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/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/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/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**Re: st: What is the effect of centering on marginal effects?***From:*Alessandro Freire <alessandro.freire@gmail.com>

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