On Mon, 3 Nov 2008, J. Sebastian Tello wrote:
Does anyone know of a literature reference, or a piece of code that can
help me calculate the amount of variation explained (R2 value), in a
regression constrained to have a slope of 1 and an intercept of 0?
Sebastien,
In the future, please follow the posting guide or use help.request() to
craft a better posting to this list.
Something like this is what you are after?
x <- rnorm(100)
y <- rnorm(100,x)
# unexplained
sum(residuals(lm(y~0+offset(x)))^2)/sum(y^2)
[1] 0.500178
(sum(y^2) - sum( residuals( lm(y~0+offset(x)) )^2))/sum(y^2)
[1] 0.499822
Of course, I could have finessed the use of lm(), but why pass up an
opportunity to show how the formula language handles this?
---
Be advised that this (fixing values of coefficients in tow models and
then comparing them) is a tricky business.
You can get 'explained' values that are not in [0,1], which is a source of
confusion to many. You can use
RSiteSearch("R2 intercept")
to find threads on this.
The usual distribution theory for nested linear models does not apply.
(Read: do not try to compute a p-value unless you have the assistance of a
statistician who can explain this sentence.)
HTH,
Chuck
Thanks!
Sebastian
J. Sebasti?n Tello
Department of Biological Sciences
285 Life Sciences Building
Louisiana State University
Baton Rouge, LA, 70803
(225) 578-4284 (office and lab.)
[[alternative HTML version deleted]]
Charles C. Berry (858) 534-2098
Dept of Family/Preventive Medicine
E mailto:[EMAIL PROTECTED] UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego 92093-0901
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