Re: [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

Cec�lia 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
	[[alternative HTML version deleted]]

______________________________________________
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
 

______________________________________________
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help