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From |
Maarten buis <maartenbuis@yahoo.co.uk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: AW: st: AW: beta coefficients for interaction terms |

Date |
Tue, 21 Apr 2009 17:27:14 +0000 (GMT) |

Yes, but on a general note: don't try to interpret interaction effects without writing down the equation and doing some computations on paper. When doing interactions I always use my whiteboard and compute the effects for several values of the variables. I have never been able to properly interpret interaction terms without writing down the effects. -- Maarten ----------------------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://home.fsw.vu.nl/m.buis/ ----------------------------------------- --- On Tue, 21/4/09, lschoele@rumms.uni-mannheim.de <lschoele@rumms.uni-mannheim.de> wrote: > From: lschoele@rumms.uni-mannheim.de <lschoele@rumms.uni-mannheim.de> > Subject: Re: AW: st: AW: beta coefficients for interaction terms > To: statalist@hsphsun2.harvard.edu > Date: Tuesday, 21 April, 2009, 5:17 PM > Thank you very much Maarten. > So for the interpration of the beta coefficicients: > For example Y=5.09-2.30X+4.50Z+1.20XZ > The interpretion for my interaction term would be: the > interaction > lowers the negative effect of X and it increases the > positiv effect of > Z. Am I getting it right? > > Lisa > > Zitat von Maarten buis <maartenbuis@yahoo.co.uk>: > > > > > --- On Tue, 21/4/09, lschoele@rumms.uni-mannheim.de > wrote: > >> Without having iteraction terms, as far as I know > you have > >> to coed -regress, beta- to get the standardised > beta > >> coefficients, so you can tell which variable has > the > >> biggest effect. > > > > With interactions you have to very precise about what > you > > exactly want. The whole point of an interaction is > that > > the effect of a variable is allowed to change when > > another variable changes. So the question which > variable > > has the bigger effect now has multiple answers. > > > > The way forward is to go back to your substantive > problem > > and try to figure out what it is exactly what you want > to > > know, and derive your interaction term and > standardizations > > from that. > > > > One way that could make sense is to present the > difference > > between standardized effects for different values of > both > > variables in a graph like in the example below: > > > > *------------------------ begin example > ------------------- > > sysuse auto, clear > > local vlist "price mpg rep78" > > foreach var of varlist `vlist' { > > sum `var' > > qui gen double z_`var' = (`var' - > r(mean))/r(sd) > > } > > gen z_mpgXz_rep78 = z_mpg*z_rep78 > > > > > > reg z_price z_mpg z_rep78 z_mpgXz_rep78 > > > > gen effdif0 = _b[z_mpg] + _b[z_mpgXz_rep78]* z_mpg - > /// > > (_b[z_rep78]) > > > > gen effdif_2 = _b[z_mpg] + _b[z_mpgXz_rep78]* z_mpg - > /// > > (_b[z_rep78] + _b[z_mpgXz_rep78]*-2) > > > > gen effdif2 = _b[z_mpg] + _b[z_mpgXz_rep78]* z_mpg - > /// > > (_b[z_rep78] + _b[z_mpgXz_rep78]*2) > > > > twoway line effdif_2 effdif0 effdif2 mpg, sort /// > > ytitle("difference in standardized > effects" /// > > "of mileage and repair status") > /// > > legend(order(1 "z_rep78 = -2" > /// > > 2 "z_rep78 = 0" > /// > > 3 "z_rep78 = 2")) > /// > > yline(0) > > *------------------- end example > -------------------------- > > > > Hope this helps, > > Maarten > > > > ----------------------------------------- > > Maarten L. Buis > > Institut fuer Soziologie > > Universitaet Tuebingen > > Wilhelmstrasse 36 > > 72074 Tuebingen > > Germany > > > > http://home.fsw.vu.nl/m.buis/ > > ----------------------------------------- > > > > > > > > > > > > > > * > > * 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: AW: st: AW: beta coefficients for interaction terms***From:*lschoele@rumms.uni-mannheim.de

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