[R] factorial design

[Spencer Graves]

The first model includes C and interactions with C, which are combined 
with the residuals in the other two models.  The first model has 3, 3, 
3, 3, and 32 degrees of freedom for C, A:C, B:C, A:B:C, and residuals, 
respectively.  The other two models combine these two into a single 
residual term with 44 = 3 + 3 + 3 + 3 + 32 degrees of freedom. 

hope this helps.  spencer graves

Cecília Shiraiwa wrote:

>    Hello all,
>    I´m trying to study a factorial design, but I can´t understand why did Df, Sum Sq and Mean Sq of residuals alter when I Split the interaction? I think that Split the interaction must not alter the residuals. Am I doing something wrong?
>    Could anyone help me?
>    My data and functions I tried are:
> 
>Y<-c(196,213,183,
>        192,253,199,
>        251,331,276,
>        128,220,196,
>        272,275,227,
>        204,305,185,
>        135,322,276,
>        262,284,250,
>        272,275,227,
>        204,305,185,
>        135,322,276,
>        262,284,250,
>        296,369,344,
>        325,396,403,
>        370,323,319,
>        341,418,318)
>A<-factor(rep(c(0,1),c(24,24)))
>B<-factor(rep(c(0,1,0,1),c(12,12,12,12)))
>C<-factor(rep(c(rep(0:3,each=3)),times=4))
>av <- aov(Y ~ A + B + A*B + C + A*C + B*C + A*B*C )
>summary(av)
>avAB <- aov(Y ~ A/B)
>summary (avAB, split=list("A:B"=list(A1=1, A2=2)))
>avBA <- aov(Y ~ B/A)
>summary (avBA, split=list("B:A"=list(B1=1, B2=2)))
>
>
>Thanks
>Cecilia
>
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