Thank you very much, Douglas, for the reply,

this

Rt.lmer <- lmer(RT ~ S * R * T + (1|Subject) + (1|Subject:S:R:T), ...)

is not working, however, and gives the error

Error in lmerFactorList(formula, mf, fltype) : number of levels in 
grouping factor(s) 'S:R:T:Subj' is too large

I do have many subjects (~100) - is that a problem?


Also, you wrote that

If you want to express Subject:Condition in terms of Subject, S, R and
T then you just need to generate a factor with a separate level for
each distinct combination of Subject, S, R and T, which is what
Subject:S:R:T is.

I take this to mean that

Rt.lmer <- lmer(RT ~ S * R * T + (1|Subject) + (1|Subject:S:R:T), ...)

is equivalent to

RT.lme <- lme(RT ~ Condition, random = ~1 | Subject/Condition, Data)

...with Condition an 8-level factor - 1 level for each S R T combination.

However, (and I'm REALLY sorry to bring the old "but according to 
SPSS/SAS/Statistica" argument), in my Statistica-coined experience 
the results of a post-hoc test differ if one puts in 1 8-level factor 
vs. 3 2-level factors. Am I missing something?


Thanks again,

Ulli




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