Estimated Effects Not Balanced
Hi, Thanks Richard, That was me playing with too many examples and having too many variables just lying around. Thanks for the tip though.
On 22 August 2016 at 23:32, Bert Gunter <bgunter.4567 at gmail.com> wrote:
Thanks, Rich. I didn't notice that! -- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Mon, Aug 22, 2016 at 1:43 PM, Richard M. Heiberger <rmh at temple.edu> wrote:
The problem is that you have 12 observations and 1+2+10=13 degrees of
freedom.
There should be 1 + 2 + 8 = 11 degrees of freedom. Probably one of your variables is masked by something else in you
workspace.
Protect yourself by using a data.frame
tmp <- data.frame(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, data=tmp) summary(mod)
Df Sum Sq Mean Sq F value Pr(>F) A 1 1.553 1.553 1.334 0.281 B 2 3.158 1.579 1.357 0.311 Residuals 8 9.311 1.164 On Mon, Aug 22, 2016 at 11:15 AM, Justin Thong <justinthong93 at gmail.com>
wrote:
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
*I check my email at 9AM and 4PM everyday*
*If you have an EMERGENCY, contact me at +447938674419(UK) or
+60125056192(Malaysia)*
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______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/
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and provide commented, minimal, self-contained, reproducible code.
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/
posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Yours sincerely, Justin *I check my email at 9AM and 4PM everyday* *If you have an EMERGENCY, contact me at +447938674419(UK) or +60125056192(Malaysia)* [[alternative HTML version deleted]]