On Feb 9, 2010, at 6:33 PM, bluesky...@gmail.com wrote:
The model matrix for the code at the end the email is shown below.
Since the model matrix doesn't have -1, I think that it is made of
dummy regressors rather than deviation regressors. I'm wondering how
to make a model matrix using deviation regressors. Could somebody let
me know?
If I understand your terminology, then:
?contr.sum
--
David.
model.matrix(aaov)
(Intercept) A2 B2 B3 A2:B2 A2:B3
1 1 0 0 0 0 0
2 1 0 0 0 0 0
3 1 0 0 0 0 0
4 1 0 0 0 0 0
5 1 1 0 0 0 0
6 1 1 0 0 0 0
7 1 1 0 0 0 0
8 1 1 0 0 0 0
9 1 0 1 0 0 0
10 1 0 1 0 0 0
11 1 0 1 0 0 0
12 1 0 1 0 0 0
13 1 1 1 0 1 0
14 1 1 1 0 1 0
15 1 1 1 0 1 0
16 1 1 1 0 1 0
17 1 0 0 1 0 0
18 1 0 0 1 0 0
19 1 0 0 1 0 0
20 1 0 0 1 0 0
21 1 1 0 1 0 1
22 1 1 0 1 0 1
23 1 1 0 1 0 1
24 1 1 0 1 0 1
attr(,"assign")
[1] 0 1 2 2 3 3
attr(,"contrasts")
attr(,"contrasts")$A
[1] "contr.treatment"
attr(,"contrasts")$B
[1] "contr.treatment"
#############
a=2
b=3
n=4
A = rep(sapply(1:a,function(x){rep(x,n)}),b)
B = as.vector(sapply(sapply(1:b, function(x){rep(x,n)}), function(x)
{rep(x,a)}))
Y = A + B + rnorm(a*b*n)
fr = data.frame(Y=Y,A=as.factor(A),B=as.factor(B))
aaov=aov(Y ~ A * B,fr)
summary(aaov)
model.matrix(aaov)
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David Winsemius, MD
Heritage Laboratories
West Hartford, CT
______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
