From: <Richard.Cotton_at_hsl.gov.uk>

Date: Thu, 29 May 2008 17:30:48 +0100

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Thu 29 May 2008 - 17:57:40 GMT

Date: Thu, 29 May 2008 17:30:48 +0100

> I'm attempting to plot a cubic relationship between two variables

*> controlling for the effects of a third variable. In this short
**> example, I'm trying to use AGE to predict CORTEX while controlling for
**> the effects of TIV (total intracranial volume):
**>
**> ########################
**> cortex = rnorm(100, mean=0.5, sd=0.5)
**> age = rnorm(100, mean=10, sd=2)
**> tiv = rnorm(100, mean=1000, sd=100)
**>
**> ##
**> ## simple regression (ignoring TIV) works
**> ##
**> cortex.lm = lm(cortex ~ poly(age, degree=3))
**> plot(age, cortex)
**> pseudo.x = seq(min(age)-2, max(age)+2, len=200)
**> lines(pseudo.x, predict(cortex.lm, data.frame(age=pseudo.x)))
**>
**> ##
**> ## multiple regression (accounting for TIV) fails
**> ##
**> cortex.lm = lm(cortex ~ poly(age, degree=3) + tiv)
**> plot(age, cortex)
**> pseudo.x = seq(min(age)-2, max(age)+2, len=200)
**> lines(pseudo.x, predict(cortex.lm, data.frame(age=pseudo.x)))
**> ########################
**>
**> Although the last 'lines' command fails, summary(cortex.lm) does give
**> me reasonable coefficients for the multiple regression. Can anyone
**> advise me if (1) this is at all a legitimate procedure, and (2) how to
**> draw the cubic function that fits the multiple regression?
*

Regards,

Richie.

Mathematical Sciences Unit

**HSL
**

R-help_at_r-project.org mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Thu 29 May 2008 - 17:57:40 GMT

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