Dear Colleagues,
I have what Roger Kirk (Experimental Design: Procedures for the Behavioral
Sciences, 1968) refers to as a randomized block factorial design.  The anova
table would look like this:

                      df
A                     3
Subj/A          103 (error term for A)
B                   23
A*B                69
B*Subj/A     2369 (error term for B and A*B)

Subjects are nested within A and give a response for each B.  If y is the
dependent variable, is this the correct lmer specification for the above,
where ID is the variable name for Subj:

lmer(y ~ A + B + A*B + (A|ID))

Am I barking up the right tree?  I can also fit:

aov(y ~ A + B + A*B  + ID)
then I have to do some hand calculations to use ID as the error term for A.
 The residual (really B*ID) is the correct error term for B and A*B.

Thanks,

Larry

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