[R] Model matrix using dummy regressors or deviation regressors
David Winsemius
dwinsemius at comcast.net
Wed Feb 10 00:47:11 CET 2010
On Feb 9, 2010, at 6:33 PM, bluesky315 at 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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> and provide commented, minimal, self-contained, reproducible code.
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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