[R] Unexpected results using the oneway_test in the coin package

[David Winsemius]

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.Hothorn at 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
>
>
>
>
>
>
> 	[[alternative HTML version deleted]]
>
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David Winsemius, MD
West Hartford, CT