similar to: Post-hoc test for Kruskal-Wallis

Dear all, I run a kruskal wallis test and found significant results. Then, I conducted all pairwise comparisons and found no significant results. Could anyone please give me a hint as to why this happens or redirect me towards a specific web page where I can find more info? (I used alpha=5% and made no bonferroni or other correction for the pairwise comparisons) Thank you   Dr. Iasonas

Hi, I have searched and found a response to a question similar to mine but when I tried the code, R says it's not an actual function so I thought I'd ask here. http://r.789695.n4.nabble.com/file/n4633035/Cookies.csv Cookies.csv I have attached the data I am using. I am trying to look at two things: how moisture content changes over time, and how it changes along the length of a log

Hi there, I am doing multiple comparisons for data that is not normally distributed. For this purpose I tried both functions kruskal{agricolae} and kruskalmc{pgirmess}. It confuses me that these functions do not yield the same results although they are doing the same thing, don't they? Can anyone tell my why this happens and which function I can trust? kruskalmc() tells me that there are no

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

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

Hi all, After running kruskal.test I have got results (p<0,005) pointing to reject the hypothesis that the samples were draw from the same population. Howerver when I run the kruskalmc there are no significant differences in any of the multiple comparisons. Is that possible? Some clarification? Thanks, Humber <https://sites.google.com/site/humberandrade> [[alternative HTML version

Dear list! I work with multiple Kruskal-Wallis test (kruskalmc, package pgirmess), which evaluates differences in medians among groups (5 groups). A result of a test is significant differences among some groups, while median values are the same for 4 groups (using tapply). Why? p.s.: number of samples in groups vary from 50 to 4900. Thanks to all, OV .

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

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

Hello. We have some questions concerning the statistical analysis of a dataset. We aim to compare the sample means of more than 2 independent samples; the sample sizes are unbalanced. The requirements of normality distribution and variance homogeneity were not met even after transforming the data. Thus we applied a nonparametric test: the Kruskal-Wallis-test (H-Test). The null hypothesis was

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

Hi, I have got two groups of samples; and for every row, I wish to calculate Kruskal-Wallis' p-value. In the example below, and the stars (****) show where I am struggling to design and put things together. Any help would be appreciated. myFile <- data.frame(Sample_1a = 1:10, Sample_1b = 2:11, Sample_1c = 3:12, Sample_2a=4:13, Sample_2b=7:16, row.names=LETTERS[1:10]) groups <- rep

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 interested in using "multcompLetters" after running "kruskalmc" but I'm a newbie and I'm not having luck figuring it out. I can run "kruskalmc" just fine, but after studying the documentation for "multcompletters" for a long time, I cannot figure out how to make it work. Any ideas? R input is below > >> #here is my data set >>

Hi everyone, I am working on analyzing spectra which requires hundreds of kruskal wallis tests to be performed. Once significant results are found post tests are performed ect. My questions are: how do I perform all these kw tests and save just the pvalues in a table? Is there anyway to have R automatically perform post tests if a result of p<0.05 is found? Currently when I run the test

Hello, Is there like the kruskal wallis test in relation to ANOVA (no restrictions on normallity and variance homogenity) something (in R) for MANOVA? thanks -- Dr.Nicolaas Busscher Universit?t GH Kassel Nordbahnhofstrasse: 1a, D-37213 Witzenhausen Phone: 0049-(0)5542-98-1715, Fax: 0049-(0)5542-98-1713

Hi all, The Kruskal-Wallis test is a generalization of the two-sample Mann-Whitney test to *k* samples. That being the case, the Kruskal-Wallis test with *k*=2 should give an identical p-value to the Mann-Whitney test, should it not? x1<-c(1:5) x2<-c(6,8,9,11) a<-wilcox.test(x1,x2,paired=FALSE) b<-kruskal.test(list(x1,x2),paired=FALSE) a$p.value [1] 0.01587302 b$p.value [1]

Hello All, I want "Ranks' Table in R as like in SPSS ouput in the given link. http://www.statisticssolutions.com/methods-chapter/statistical-tests/kruskal-wallis-test/ Is the code is already available? Please let me know. Thanks, Lawrence

Dear listers, I was used to package pgirmess under Windows with everything OK, but, for the first time, I had a trial this afternoon on Ubuntu 7.10 gutsy (I have a double boot computer and work more and more under unix) and R 2.7.0. Everything went OK except this: sudo R CMD check pgirmess ..... * checking examples ... ERROR Running examples in 'pgirmess-Ex.R' failed. The error most

Hola. Llevo poco tiempo con R y estoy atascado en un problemilla, a ver si podéis ayudarme. Estoy trabajando con una base de datos sobre personalidad en diferentes especies de aves. Esta base tiene datos de más de 7000 individuos y me gustaría crear un bucle mediante el cual realizar un test de Kruskal Wallis por cada especie (quiero ver si los comportamientos son consistentes dentro de cada