[R] general question about plotting multiple regression results
tlumley at u.washington.edu
Thu Apr 19 16:37:28 CEST 2007
On Thu, 19 Apr 2007, Simon Pickett wrote:
> 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.
termplot() does this for a range of regression models (without interaction
terms). The "effects" package does it better for linear regression models.
> Here is an example illustrating my problem
> 1.I do a linear regression as follows
> which gives some nice sig. results
> 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
> In this case I would usually plot the fitted values values against the raw
> values of x... Is this the right approach?
> #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
> 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 Pickett
> PhD student
> Centre For Ecology and Conservation
> Tremough Campus
> University of Exeter in Cornwall
> Tel 01326371852
> R-help at stat.math.ethz.ch mailing list
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
Thomas Lumley Assoc. Professor, Biostatistics
tlumley at u.washington.edu University of Washington, Seattle
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