[R] variance component analysis for nested model

[Pascal A. Niklaus]

lme should do the job (r1,r2,r3 are your random factors):

    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
Schönbeinstrasse 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!
>
>
>  
>