The second is that I think you need R-devel which has some fixes.
However, I think this is an inappropriate analysis (which is why the older code trips up). Your analysis is equivalent to using the fixed-effects model Lab + Material on the means of each Material block. If there is something different about the replicates of the Material, this was a very poor design and so I suspect that is not what was done. It looks like a randomized block design with replication in the blocks, for which
aov(Measurement ~ Lab + Material, data = testdata)
is the appropriate analysis. In any case, there is no need of a multi-stratum analysis.
On Wed, 16 Feb 2005, Jamie Jarabek wrote:
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 <- c(12.20,12.28,12.16,15.51,15.02,15.29,18.14,18.08,18.21,18.54,18.36
,18.45,12.59,12.30,12.67,14.98,15.46,15.22,18.54,18.31,18.60,19.21,18.77
,18.69,12.72,12.78,12.66,15.33,15.19,15.24,18.00,18.15,17.93,18.88,18.12,18.03)
testdata <- data.frame(Lab,Material,Measurement) rm(list=c("Lab","Material","Measurement"))
test.aov <- with(testdata,aov(Measurement ~ Material + Error(Lab/Material)))
This gives me the desired ANOVA table. I next want to get the standard errors for certain contrasts and following the help page for se.contrast() I tried the following but I get an error:
se.contrast(test.aov,list(Material=="A",Material=="B",Material=="C",Material=="D"),coef=c(1,1,-1,-1),data=testdata)Error in matrix(0, length(asgn), ncol(effects), dimnames = list(nm[1 + : length of dimnames [1] not equal to array extent
I have tested this on R 2.0.1 on Windows XP and Solaris and get the same
error on both systems. I am unsure as to what I am doing wrong here. Thanks for any help.
Jamie Jarabek
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