Dear Prof Ripley, Dear Prof Dalgaard
Thank you both for your help. I tried it with helmert contrasts
and got a result that is consistent with lme. I didn't realize
that the parameterization of the model has an influence on the
contrasts that I tried to test.
It seems that I should read a little
On Tue, 22 Feb 2005, Christoph Buser wrote:
Dear Prof Ripley, Dear Prof Dalgaard
Thank you both for your help. I tried it with helmert contrasts
and got a result that is consistent with lme. I didn't realize
that the parameterization of the model has an influence on the
contrasts that I tried to
On Thu, 17 Feb 2005, Christoph Buser wrote:
Dear Jamie
As Prof. Ripley explained your analysis is equivalent to the fixed effect
models for the means, so you can calculate it by (if this is your design):
Lab - factor(rep(c(1,2,3),each=12))
Material - factor(rep(c(A,B,C,D),each=3,times=3))
Prof Brian Ripley [EMAIL PROTECTED] writes:
test.aov - with(testdata,aov(Measurement ~ Material +
Error(Lab/Material)))
se.contrast(test.aov,
list(Material==A,Material==B,Material==C,Material==D),
coef=c(0.5,0.5,-0.5,-0.5),data=testdata)
[1] 0.1432572
I
On Mon, 21 Feb 2005, Peter Dalgaard wrote:
Prof Brian Ripley [EMAIL PROTECTED] writes:
test.aov - with(testdata,aov(Measurement ~ Material + Error(Lab/Material)))
se.contrast(test.aov,
list(Material==A,Material==B,Material==C,Material==D),
Dear Jamie
I already thought that your data structure could be more
complicated than in the example.
I would be careful anywhere. Since there is a difference in the
results of se.contrasts() in R-devel and the results from lme
(and the with lme consistent results of the aggregated data)
in this
The first problem is that Material is undefined when you called
se.contrast, as you removed it. This may work, but it certainly is not
intentional and what variable gets picked up may not be predicted
reliably.
The second is that I think you need R-devel which has some fixes.
However, I think
Dear Jamie
As Prof. Ripley explained your analysis is equivalent to the fixed effect
models for the means, so you can calculate it by (if this is your design):
Lab - factor(rep(c(1,2,3),each=12))
Material - factor(rep(c(A,B,C,D),each=3,times=3))
Measurement -
Christoph,
Thank you for your advice. My actual design is indeed more complicated than what
I have indicated here. I was just using this as a toy example illustrate my
particular problem. As suggested by Prof. Ripley I will download R-devel and see
if the fixes included within alleviate my
I am having trouble getting standard errors for contrasts using se.contrast() in
what appears to be a simple case to me. The following test example illustrates
my problem:
Lab - factor(rep(c(1,2,3),each=12))
Material - factor(rep(c(A,B,C,D),each=3,times=3))
Measurement -
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