[R] general question about plotting multiple regression results

[Simon Pickett]

Hi all,

I have been bumbling around with r for years now and still havent come up
with a solution for plotting reliable graphs of relationships from a
linear regression.

Here is an example illustrating my problem

1.I do a linear regression as follows

summary(lm(n.day13~n.day1+ffemale.yell+fmale.yell+fmale.chroma,data=surv))

which gives some nice sig. results

Coefficients:
             Estimate Std. Error t value Pr(>|t|)
(Intercept)  -0.73917    0.43742  -1.690 0.093069 .
n.day1        1.00460    0.05369  18.711  < 2e-16 ***
ffemale.yell  0.22419    0.06251   3.586 0.000449 ***
fmale.yell    0.25874    0.06925   3.736 0.000262 ***
fmale.chroma  0.23525    0.11633   2.022 0.044868 *

2. I want to plot the effect of "ffemale.yell", "fmale.yell" and
"fmale.chroma" on my response variable.

So, I either plot the raw values (which is fine when there is a very
strong relationship) but what if I want to plot the effects from the
model?

In this case I would usually plot the fitted values values against the raw
values of x... Is this the right approach?

fit<-fitted(lm(n.day13~n.day1+ffemale.yell+fmale.yell+fmale.chroma,data=fsurv1))

plot(fit~ffemale.yell)

#make a dummy variable across the range of x
x<-seq(from=min(fsurv1$ffemale.yell),to=max(fsurv1$ffemale.yell), length=100)

#get the coefficients and draw the line
co<-coef(lm(fit~ffemale.yell,data=fsurv1))
y<-(co[2]*x)+co[1]
lines(x,y, lwd=2)

This often does the trick but for some reason, especially when my model
has many terms in it or when one of the independent variables is only
significant when the other independent variables are in the equation, it
gives me strange lines.

Please can someone show me the light?

Thanks in advance,

Simon.






Simon Pickett
PhD student
Centre For Ecology and Conservation
Tremough Campus
University of Exeter in Cornwall
TR109EZ
Tel 01326371852