Effects - plot the marginal effect

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 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 ?***? 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

	[[alternative HTML version deleted]]

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 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 ???***??? 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

	[[alternative HTML version deleted]]