Dear Tomas,
On Fri, 8 Apr 2011 10:24:45 +0200
Tomii 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 examp
On Apr 8, 2011, at 4:24 AM, Tomii wrote:
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 wrote:
Dear Tomas,
Write the model as
mreg01 = lm(enep1 ~ enpres *
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 wrote:
> Dear Tomas,
>
> Write the model as
>
> mreg01 = lm(enep1 ~ enpres * proximity1), data=a90)
>
> That is,
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 in
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$proximity1 + (a90$en
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