Thank you for your response, but these changes doesn't seem to change
anything, outcomes of effect command is still the same - error.

Tomas

On Fri, Apr 1, 2011 at 5:03 AM, John Fox <jfox@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@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 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 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
>
>
>
>

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