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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