[R] unbalanced design in multifactor anova....

Bert Gunter bgunter@4567 @end|ng |rom gm@||@com
Tue Jan 18 16:38:10 CET 2022

Please read ?aov and ?lm (and ?anova.lm). This should ordinarily be
your first port of call before posting here.
The former explicitly says:
"aov is designed for balanced designs, and the results can be hard to
interpret without balance: beware that missing values in the
response(s) will likely lose the balance. If there are two or more
error strata, the methods used are statistically inefficient without
balance, and it may be better to use lme in package nlme.

Balance can be checked with the replications function."

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, Jan 17, 2022 at 11:14 PM akshay kulkarni <akshay_e4 using hotmail.com> wrote:
> dear members,
>                          I have a question on anova as implemented in R.
> If there is an unbalanced design in multifactor anova, will aov or lm work properly? I was reading a book on excel where the author points that in an unbalanced design, the factors, as coded vectors, are correlated. He says that variance will be allocated properly only when the coded vectors are uncorrelated. But he also justifies that the function TREND() in Excel handles this automatically using semipartial correlations.
> What about aov or lm in R, which are used to implement anova? Should we do some thing extra for them to work properly in an unbalanced design? Or will the coding system used by R to represent the factors or levels internally handles the correlation?
> THanking you,
> Yours sincerely,
>         [[alternative HTML version deleted]]
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