I have been asked how to handle the following situation in R: Given an unbalanced design of 3 crossed random effects, such as subject, rater and item, how to estimate the variance components? I know how to do it using lme, but this seems to be limited to the nested case; or to use aov with error strata, when the design is balanced. -- Dipl.-Math. Wilhelm Bernhard Kloke Institut fuer Arbeitsphysiologie an der Universitaet Dortmund Ardeystrasse 67, D-44139 Dortmund, Tel. 0231-1084-257
"Wilhelm B. Kloke" <wb at arb-phys.uni-dortmund.de> writes:> I have been asked how to handle the following situation in R: > > Given an unbalanced design of 3 crossed random effects, such as > subject, rater and item, how to estimate the variance components? > > I know how to do it using lme, but this seems to be limited to > the nested case; or to use aov with error strata, when the > design is balanced.With the current version of lme it is difficult and inefficient to work with crossed random effects. A new version of lme being developed makes this much easier. I expect to release new versions of the Matrix and lme4 packages with R-1.9.0 (early April). I will describe the new lme capabilities in more detail at the useR!2004 conference in May. -- Douglas Bates bates at stat.wisc.edu Statistics Department 608/262-2598 University of Wisconsin - Madison http://www.stat.wisc.edu/~bates/