similar to: Unexpected results using the oneway_test in the coin package

Dear Researchers, Sorry for this email but I am not a statistician, and for this I have this problem to understand. Thanks in Advance for help and suggestions. Gianni I have 21 classes (00, 01, 02, 04, ....,020) with different length. I did a kruskal wall test in R with the following code kruskal.test(m.class.l, m.class.length.lf) Kruskal-Wallis rank sum test data: m.class.l and

Dear all, I've discovered the possibility to do the Nemenyi-Damico-Wolfe-Dunn test in the library(coin); oneway_test() With the given example I am unfortunately not able to reproduce the test. What does trafo and contrMat mean? I have a dataframe with 176 elements in 7 classes. It may be a problem, that my model isn't balanced? In Class1 I happen to have 4 elements, while there are 90 in

Is it possible to implement the Jonckheere-Terpstra test for ordered alternatives using the coin package: Conditional Inference Procedures in a Permutation Test Framework? I found jonckheere.test{clinfun}, but it uses a normal approximation when ties are present in the data. To make this concrete, I've include a small dataset. Thanks. --Dale Hollander and Wolfe, 1999 Table 6.6, pg 205

Dear expeRts, I would like to use a oneway_test (from package coin) to test whether two groups differ on various variables. The variables are encoded within a data frame. Unfortunately, I obtained an error, that I don't understand. Could you please help me ? Example: library(coin) y <- as.data.frame(matrix(rnorm(200), ncol=2)) group <- as.factor(unif(100)) lapply(y,

Dear R users, I would like to know if there is a way in R to execute a post-hoc test (factor levels comparison, like Tukey for ANOVA) of a non-parametric analysis of variance with kruskal.test() function. I am comparing three different groups. The preliminary analysis using the kruskal-wallis-test show significance, but I still don''t know the relationship and the significance level

Dear R users, I am trying to apply the analysis processed in a paper, on the data I'm working with. The data is: 80 patients for which I have survival data (time - days, and event - binary), and microarray expression data for 200 genes (predictor continuous variables). My data matrix "data.test" has ncol: 202 and nrow: 80. What I want to do is: - run recursive partitioning on

Hi, I'm trying to run a permutation test on paired samples. First I tried the package "exactRankTests": require("exactRankTests") x <- c(1.83,0.50,1.62,2.48,1.68,1.88,1.55,3.06,1.30) y <- c(0.878,0.647,0.598,2.05,1.06,1.29,1.06,3.14,1.29) wilcox.test(x,y,paired = TRUE,alternative = "greater") perm.test(y,x,paired = TRUE,exact = TRUE,alternative =

Dear R users: I have been trying to figure out how to include string variables in a for loop to run multiple random forests with little success. The current code returns the following error: Error in trafo(data = data, numeric_trafo = numeric_trafo, factor_trafo = factor_trafo, : data class character is not supported In addition: Warning message: In storage.mode(RET@predict_trafo) <-

Hi list, I would like to know if there is a way in R to execute a post-hoc test (factor levels comparison, like Tukey for ANOVA) of a non-parametric analysis of variance (kruskal.test() function object). I was looking for something like the Dunn Test. I’ve searched the internet but nothing seemed to define a way to it. Do You have any suggestion? Other equivalent test maybe! Thanks in

I am trying to do a Nonparametric Tukey-type multiple comparison post-hoc test to determine which groups are significantly different. I have read the dialogue on this topic from the R-help, and am still not clear why no statistical packages include this test as an option? Is it not an appropriate test to conduct on non-normally distributed data? Is the only option to calculate it by hand

It seems that MASS suggest to judge on the basis of sum(residuals(mode,type="pearson"))/df.residual(mode). My question: Is there any rule of thumb of the cutpoiont value? The paper "On the Use of Corrections for Overdispersion" suggests overdispersion exists if the deviance is at least twice the number of degrees of freedom. Are there any further hints? Thanks. -- Ronggui

Using the package ?exactRankTests? one can execute a one-sample permutation test for a hypothesized location parameter of 0 like: perm.test(rnorm(30,0)) The package ?exactRankTests? seems now to be deprecated in favor of the ?coin? package which as I understand is a superset of ?exactRankTests? in terms of functionality. The ?coin? package allows one to run a two-sample permutation test using

Dear list, I tried to use the nparcomp to run some post hoc non-parametric comparison and got and error. Error in uniroot(pfct, interval = interval) : f() values at end points not of opposite sign Appreciate any comments. the command line: >nparcomp(Ulceration~Group,data=test,type='Dunnett',control='Non-treated') Jun

Hi R users! I have the following problem: how appropriate is my aov model under the violation of anova assumptions? Example: a<-c(1,1,1,1,1,1,1,1,1,1,2,2,2,3,3,3,3,3,3,3) b<-c(101,1010,200,300,400, 202, 121, 234, 55,555,66,76,88,34,239, 30, 40, 50,50,60) z<-data.frame(a, b) fligner.test(z$b, factor(z$a)) aov(z$b~factor(z$a))->ll TukeyHSD(ll) Now from the aov i found that my model

I am trying to do a Nonparametric Nemenyi test for multiple comparison in a two way layout data because I need to know the exact distribution. I don?t know if this test is in the R software. I just found a Nemenyi test for a one way design. But in Hollander book the Nemenyi test is in page 253 for to way layout data. Thank you for your help.

Sorry if this subject has been already dealt here. Which are some common tests for nonparametric k-way ANOVA? I have read about Kruskal-Wallis test as a kind of nonparametric one-way ANOVA, but I have not found anything about a general-setting (I mean k-way) nonparametric ANOVA. Can you recommend me a good R package (or other reliable software) for that? Looking forward to your answers, --

I have insect data from twelve sites and like most environmental data it is non-normal mostly. I would like to preform an anova and a means seperation like tukey's HSD in a nonparametric sense (on some sort of central tendency measure - median?). I am searching around at this time on the internet. Any suggestions, books, etc. would be greatly appreciated. -- Stephen Sefick Research

Hi folks, sorry if this has been answered before, I searched long and hard before deciding to make a thread. I'm trying to include multiple variables in a non-parametric analysis (hah!). So far what I've managed to figure out is that the NPMC package from CRAN MIGHT be able to do what I need, but I can't get it to. First I created a dataset as NPMC calls for. > Ind=Individual

Hello, I need nemenyi-test or any other post-hoc test for kruskal-wallis, but I just can't find out how to implement this in R. My data set is nitrite concentrations in four different groups which I intend to compare. The kruskal-wallis-test showed significance, but I still don't know between which groups these significances are. Can anybody help me with this? Thanks

Hi there, I've got a small question : is there any post-hoc test for Kruskal rank sum test integrated in R ? I know that the Nemenyi test is one of the post-hoc that can be used, but there's no (to by knowledge) R function for it. What should I do ? Thanks, Etienne