The usual way to pose questions about "unexpected behavior" is to look
up the package maintainer's name and email address in the DESCRIPTION
file of the package which is accessed with the help function:
help(package=coin)
You see:
Maintainer: Torsten Hothorn <torsten.hoth...@r-project.org>
--
David
On Jan 9, 2012, at 4:48 AM, Christoph Liedtke wrote:
Dear fellow R users,
Keywords: Kruskal-Wallis, Post-Hoc, pair-wise comparisons, Nemenyi-
Damico-Wolfe-Dunn test, coin package, oneway_test
I am using the "oneway_test" function in the R package "coin" and I
am obtaining results which I cannot believe are accurate. I do not
wish to waste anyone's time and so if the following problem is
rather trivial, I apologize, however I could not seem to resolve my
problem with an online search and I am fresh out of ideas.
I have carried out a Kruskal-Wallis test to compare breeding
strategy variance of my study organisms (rank data, therefore non-
parametric, in oder of increasing degree of "terrestrialization", in
this case: adaptations to breeding on land as opposed to in aquatic
habitats) between habitat groups (I, II and III). Subsequently I
would like to do a "Post-Hoc test" or in other words a set of
corrected pair-wise comparisons to test the relationship between
individual groups. For this I would like to use the Nemenyi-Damico-
Wolfe-Dunn test in the "coin" package (aka oneway_test). However,
when I apply it to my data, I receive highly significant differences
between all of my groups, which when looking at my data, cannot be
true. I have posted one of my command blocks below containing my
data set as well as the script adapted from the coin package manual.
library(coin)
library(multcomp)
###this is my data:
mydata <- data.frame(breeding =
c(4,4,4,4,1,1,1,1,8,8,8,8,9,7,7,4,4,4,6,1,1,1,1,1,1,4,1,4,4,1,1,4,4,1,1,1,1,6,6,6,6,6,2,2,2,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,11,7,1,1,1,1,1,4,4,4,4,1,1,1,1,8,8,8,8,8,8,8,8,8,8,8,8,8,9,9,9,9,9,9,7,7,7,7,7,7,7,7,7,7,5,5,5,5,5,4,4,6,6,6,6,6,6,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,3,3,3,1,4,1,7,7,7,7,7,7,12,12,12,12,12,12,1,4,7,4,1,1,1,1,1,1,1,1,4),
habitat = factor(c(rep("I", 68), rep("II", 89),
rep("III", 12))))
###box plot to visualize data
boxplot(breeding~habitat,data=mydata,main="Boxplot of breeding
strategies",ylab="breeding strategy",col="gold",lty=1)
### Kruskal-Wallis test
kruskal_test(breeding ~ habitat, data = mydata, distribution =
approximate(B = 9999))
### Nemenyi-Damico-Wolfe-Dunn test (joint ranking)
NDWD <- oneway_test(breeding ~ habitat, data = mydata,
ytrafo = function(data) trafo(data, numeric_trafo = rank),
xtrafo = function(data) trafo(data, factor_trafo = function(x)
model.matrix(~x - 1) %*% t(contrMat(table(x), "Tukey"))),
teststat = "max", distribution = approximate(B = 900000))
### global p-value
print(pvalue(NDWD))
### sites-by-site p values at alpha = 0.01 (page 244)
print(pvalue(NDWD, method = "single-step"))
I should be detecting some non-significance between groups I and III
at least, but the test comes back with extremely low p-values.
Where am I going wrong?
Thank you very much for your help.
With kind regards
Christoph
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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David Winsemius, MD
West Hartford, CT
______________________________________________
R-help@r-project.org mailing list
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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.
