Re: [R] "Estimate effects may be unbalanced" in aov()

[Max Manfrin]

On 22 Oct 2007, at 10:50, Prof Brian Ripley wrote:

On Mon, 22 Oct 2007, Max Manfrin wrote:

Can anybody explain me what does it mean "Estimated effects may be unbalanced", and what does it imply for the anova analysis?

Try


aov(rnorm(16) ~ A * B * C, data = D)

The help page does! I suspect you intended to use factors, and have not done so, and also that you did not intend to replicate res. D <- expand.grid(A=factor(c(0,1,2,3)),B=factor(c(0,1)),C=factor(c (0,1)))

> D
   A B C
1  0 0 0
2  1 0 0
3  2 0 0
4  3 0 0
5  0 1 0
6  1 1 0
7  2 1 0
8  3 1 0
9  0 0 1
10 1 0 1
11 2 0 1
12 3 0 1
13 0 1 1
14 1 1 1
15 2 1 1
16 3 1 1
> aov(rnorm(16) ~ A*B*C, data=D)
Call:
   aov(formula = rnorm(16) ~ A * B * C, data = D)

Terms:


Estimated effects may be unbalanced
> !is.list(replications(formula=rnorm(16)~A*B*C,data=D))
[1] TRUE





Thanks in advance.


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Max MANFRIN                                 Tel.: +32 (0)2 650 3168
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> D<-expand.grid(A=factor(c(0,1,2,3)),B=factor(c(0,1)),C=factor(c (0,1))) A B C A:B A:C B:C A:B:C Sum of Squares 9.327827 0.256657 0.172870 4.054674 0.079648 3.214687 2.828070 Deg. of Freedom 3 1 1 3 3 1 3 The number of replicates for each factor is the same. I guess that the unbalanced refers to the number of observations that each level in a factor has, am I correct? For calculating HSDTukey confidence intervals for interaction plots in such unbalanced design, what should I do?

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