On 26 Oct 2003, 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?
With lme or (if balanced) aov with an Error term. There are lots of examples about, e.g. in the MASS and nlme scripts from the associated books. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
