I would be very grateful for help with devising the correct formula for an analysis with crossed random effects. The data consist of measurements of the width of a brain structure from 145 subjects, on both the right and left. So, Side is nested within Subject in a balanced design. 3 raters measured the widths. One rater measured all 145 widths twice - so there were 2 replications. One rater measured all the widths, and then re-measured a random 30% of them. One measured only a random 70% of the widths once. So, replication is nested within rater, and these random factors are highly unbalanced. I want to analyse the relationship of the widths to subject variables such as age and gender. But, I do not know how to write the correct formula for the random effects to specify how the Subject/Side structure is crossed with the Rater/Replication structure. I gather from reading Pinheiro and Bates (p163) that "The crossed random effects structure is represented in lme by a combination of pdBlocked and pdIdent objects". But, I cannot see how to extend the example in the book to fit my data. I would be very grateful for help with this. Jonathan Williams OPTIMA Clinical Fellow and Honorary Consultant Psychiatrist Dept Pharmacology Oxford University -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._