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
[[alternative HTML version deleted]]