The R script below illustrates the nested versus non-nested (crossed) random effects functionality in the R packages lme4 and nlme. Note that crossed random effects are difficult to specify in the nlme framework. Thus, I've included a back-of-the-envelope (literally a scanned image of my scribble) interpretation of the 'trick' to specifying crossed random effects for nlme functions (i.e., nlme and lme).

## This script illustrates the nested versus non-nested

## random effects functionality in the R packages lme4 (lmer)

## and nlme (lme).

library("lme4")

library("nlme")

data("Oxide")

Oxide

The R script below illustrates the nested versus non-nested (crossed) random effects functionality in the R packages lme4 and nlme. Note that crossed random effects are difficult to specify in the nlme framework. Thus, I've included a back-of-the-envelope (literally a scanned image of my scribble) interpretation of the 'trick' to specifying crossed random effects for nlme functions (i.e., nlme and lme).

## This script illustrates the nested versus non-nested

## random effects functionality in the R packages lme4 (lmer)

## and nlme (lme).

library("lme4")

library("nlme")

data("Oxide")

Oxide

Nice question.

Thanks a lot for your explanation!

I actually tried the pdBlocked and pdIdent functions and R gives the following error:

Error in nlme.formula(Accuracy ~ SSlogis(Iter, Asym, xmid, : 'random' must be a formula or list of formulae

Do you have any thoughts on that? I think I used the exact same code as you described above but maybe I'm wrong and missed something.

Thanks again!