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 [[alternative HTML version deleted]]