Estimated Effects Not Balanced

Something does not make sense in R. It has to do with the question of
balance and unbalance.

*A<-factor(c(1,1,1,1,1,1,2,2,2,2,2,2))*
*B<-factor(c(1,1,2,2,3,3,1,1,2,2,3,3))*
*y<-rnorm(12)*
*mod<-aov(y~A+B)*

I was under the impression that the design is balanced ie order does not
effect the sums of squares. However, when I compute the anova R reports
that the Estimated Effects are Unbalanced. I thought that when all
combinations of levels of A and B have equal replications then the design
is called balanced. But, R tends to think that when not all levels of A and
levels of B have equal replication, then the "Estimated Effects are
unbalanced".... Is this the same as the design being unbalanced? Because
for the example below, where the error occured, the order does not matter
(which make me think that the design is balanced).


*Call:*
*   aov(formula = y ~ A + B)*

*Terms:*
*                        A         B Residuals*
*Sum of Squares   0.872572  0.025604 16.805706*
*Deg. of Freedom         1         2        10*

*Residual standard error: 1.296368*
*Estimated effects may be unbalanced*
--
Yours sincerely,
Justin

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