library(nlme) y.lme <- lme(y ~ 1,random = ~ 1 | r1/r2/r3) summary(y.lme)
This is equivalent to a call to varcomp in S-Plus
Pascal
--
Dr. Pascal A. Niklaus Institute of Botany University of Basel Sch�nbeinstrasse 6 CH-4056 Basel / Switzerland
Russell Senior wrote:
Given a set of data:
names(data)[1] "city" "house" "visit" "value"
I am looking for a way to compute the variance components of the nested model (ie, visit 1 at house 2 at city 3 isn't related to visit 1 and house 2 at city 4), but different houses in the same city may be related, and different visits to the same house are probably related. I want to be able to compute how much of the total variance of "value" is explained by each of these. How can I do that in R?
Thanks!
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