Dear all, I am new to R and would like your help with lme formula for partially crossed random effect in a random-intercept, random-slope model. In the longitudinal data I have, each subject (barring some dropouts) was tested at 5 different occasions. The standardized tests were administered by 3 different examiners, with 2 of them present at all occasions, and the 3rd one administering tests only on the last two occasions. The subjects were randomly assigned to the examiners. I tested the following models: model1<-lme(score~time*covariate,random=~time|subject,method="REML",na.action=na.omit,data=dat) model2<-lme(score~time*covariate,random=list(examiner=~1,subject=~time),method="REML",na.action=na.omit,data=dat)
anova(model1,model2) gives p<0.05 with better model fit for model2. I would like to know if model2 is the correct way to specify the partially crossed random effect in the data I described. thanks! Pradeep Babu [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.