Dear all I have a model that looks like this:
m1 <- lmer(Difference ~ 1+ (1|Examiner) + (1|Item), data=englisho.data) I know it is not possible to estimate random effects but one can obtain BLUPs of the conditional modes with re1 <- ranef(m1, postVar=T) And then dotplot(re1) for the examiner and item levels gives me a nice prediction interval. But I would like to have the prediction interval for the individual intercepts, not the conditional modes of the random effects, that is, the fixed effect (overall estimated intercept) + the conditional mode of the random effect (examiner or item level). Does this make sense? And if so, how would I calculate this? I'd like to do the same thing to obtain prediction intervals of individual growth rates in longitudinal models (i.e., overall growth rate + random effect). Many thanks for your help, Daniel ______________________________________________ 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.
