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, [email protected] <[email protected]> wrote:
> From: [email protected] <[email protected]>
> Subject: Re: AW: st: AW: beta coefficients for interaction terms
> To: [email protected]
> 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 <[email protected]>:
>
> >
> > --- On Tue, 21/4/09, [email protected]
> 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/
> >
> >
>
>
>
> *
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