[R] Effects - plot the marginal effect
John Fox
jfox at mcmaster.ca
Fri Apr 8 15:29:42 CEST 2011
Dear Tomas,
On Fri, 8 Apr 2011 10:24:45 +0200
Tomii <diogenas at gmail.com> wrote:
> Thank you for your response, but these changes doesn't seem to change
> anything, outcomes of effect command is still the same - error.
It's not really possible to help you with so little information; if you send a reproducible example, I can try to figure out what's wrong. This time you didn't even send the command you tried to execute and the error message that it produced. (David Winsemius has already corrected a typo in my previous message.)
Best,
John
>
> Tomas
>
> On Fri, Apr 1, 2011 at 5:03 AM, John Fox <jfox at mcmaster.ca> wrote:
>
> > Dear Tomas,
> >
> > Write the model as
> >
> > mreg01 = lm(enep1 ~ enpres * proximity1), data=a90)
> >
> > That is, it's not necessary to index a90 as a list since it's given as the
> > data argument to lm, and doing so confuses the effect() function. Also,
> > enpres*proximity1 will include both the enpres:proximity1 interaction and
> > enpres + proximity1, which are marginal to the interaction.
> >
> > Next, you must quote the name of the term for which you want to compute
> > effects, thus "enpres:proximity1" in the call to effect().
> >
> > Finally, effect() doesn't compute what are usually termed marginal effects.
> > If you want more information about what it does, see the references given in
> > ?effect.
> >
> > I hope this helps,
> > John
> >
> > ------------------------------------------------
> > John Fox
> > Sen. William McMaster Prof. of Social Statistics
> > Department of Sociology
> > McMaster University
> > Hamilton, Ontario, Canada
> > http://socserv.mcmaster.ca/jfox/
> >
> > On Thu, 31 Mar 2011 22:09:32 +0200
> > Tomii <diogenas at gmail.com> wrote:
> > > Hello,
> > >
> > > I try to plot the marginal effect by using package "effects" (example of
> > the
> > > graph i want to get is in the attached picture).
> > > All variables are continuous.
> > >
> > > Here is regression function, results and error effect function gives:
> > >
> > > > mreg01 = lm(a90$enep1 ~ a90$enpres + a90$proximity1 + (a90$enpres *
> > a90$proximity1), data=a90)> summary(mreg01)
> > > Call:
> > > lm(formula = a90$enep1 ~ a90$enpres + a90$proximity1 + (a90$enpres *
> > > a90$proximity1), data = a90)
> > >
> > > Residuals:
> > > Min 1Q Median 3Q Max
> > > -2.3173 -1.3349 -0.5713 0.8938 8.1084
> > >
> > > Coefficients:
> > > Estimate Std. Error t value Pr(>|t|)
> > > (Intercept) 4.2273 0.3090 13.683 < 2e-16 ***
> > > a90$enpres 0.4225 0.2319 1.822 0.072250 .
> > > a90$proximity1 -3.8797 1.0984 -3.532 0.000696 ***
> > > a90$enpres:a90$proximity1 0.8953 0.4101 2.183 0.032025 *
> > > ---
> > > Signif. codes: 0 â€˜***â€™ 0.001 â€˜**â€™ 0.01 â€˜*â€™ 0.05 â€˜.â€™ 0.1 â€˜ â€™ 1
> > >
> > > Residual standard error: 2.029 on 78 degrees of freedom
> > > Multiple R-squared: 0.2128, Adjusted R-squared: 0.1826
> > > F-statistic: 7.031 on 3 and 78 DF, p-value: 0.0003029
> > > > plot(effect(a90$enpres:a90$proximity1, mreg01))Warning messages:1: In
> > a90$enpres:a90$proximity1 :
> > > numerical expression has 82 elements: only the first used2: In
> > > a90$enpres:a90$proximity1 :
> > > numerical expression has 82 elements: only the first used3: In
> > > analyze.model(term, mod, xlevels, default.levels) :
> > > 0 does not appear in the modelError in
> > > plot(effect(a90$enpres:a90$proximity1, mreg01)) :
> > > error in evaluating the argument 'x' in selecting a method for function
> > 'plot'
> > >
> > > >
> > >
> > > Thanks in advance.
> > > Tomas
> >
> >
> >
> >
>
> [[alternative HTML version deleted]]
>
------------------------------------------------
John Fox
Sen. William McMaster Prof. of Social Statistics
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
http://socserv.mcmaster.ca/jfox/
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