similar to: significant results with KW but not in post-hoc test

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

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 .

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, 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

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 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

Hi, i?ve read all that i could about the post-hoc test for kruskall-Wallis, now i know that i need to run Duncan test, but i?m not able to find in any package or script. I s anybody knows where can i find it? Thanks ----- Mario Garrido Escudero PhD student Dpto. de Biolog?a Animal, Ecolog?a, Parasitolog?a, Edafolog?a y Qca. Agr?cola Universidad de Salamanca -- View this message in context:

Hi, I would like to find out if the kruskalmc command in the pgirmess package controls for the family-wise type-I error rate. Thank you Dr. Iasonas Lamprianou Assistant Professor (Educational Research and Evaluation) Department of Education Sciences European University-Cyprus P.O. Box 22006 1516 Nicosia Cyprus Tel.: +357-22-713178 Fax: +357-22-590539 Honorary Research Fellow Department of

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

Recently, I ran a series of Kruskal-Wallace tests [kruskal.test()] using by() to group by site Output is a list: >Herb.KW Herb.df$ID: 10-1 Kruskal-Wallis rank sum test data: Indicator_Rating by Year Kruskal-Wallis chi-squared = 15.24, df = 7, p-value = 0.03302 ----------------------------------------------------------------------------------------------------- Herb.df$ID: 18-1

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

I followed the threads that enquired about doing post-hoc tests after doing Kruskal testing. It took me to npmc. But npmc is giving an output I do not understand. I noticed a thread entitled "npmc function: 'x' must be atomic" but there never appeared to be a resolution. > npmc(npmcinput) Error in sort(unique.default(x), na.last = TRUE) : 'x' must be atomic

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

This is only partly an R question, but this seems a good place to ask. Like many, if not most, statistics programs, R has no post hoc tests for Kruskal Wallis or Friedman, and as far as I can make out they are not available in any of the R packages. I would be grateful if someone could point me in the right direction if I am wrong. As I said this is not uncommon. Parametric Anova procedures

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

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

Hi all My data table (g) contains a continues data column (plant.height) and other columns (columns 8 to 57), each with number of levels of different factors. ANOVA test was done and the p-values were extracted as follos: a <- function(x) anova(lm(plant.height ~ x))$"Pr(>F)"[1] r<- apply(g[,8:57],2,a) If I try to do a Kruskal-Wallis test : kw <- function(x)

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

Hola, tenemos como equivalencia no paramétrica al Anova de 1 vía el test Kruskal Wallis, pero ¿existe un test no paramétrico equivalente al Anova de 2 vías? Gracias. Saludos. -- Sec. Apoyo Estadístico. Servicio de Apoyo a la Investigación (SAI) Vicerrectorado de Investigación e Internacionalización. Universidad de Murcia Edif. SACE. Campus de Espinardo. 30100 Murcia @. mariaelvira.ferre en

Hi all, I am performing hundreds of kruskal wallis tests and trying to figure out how to create a file of the p.values I obtain. This is the code I use for the tests: A2<-kruskal.test(X2~treatment) A3<-kruskal.test(X3~treatment) A4<-kruskal.test(X4~treatment) A5<-kruskal.test(X5~treatment) A6<-kruskal.test(X6~treatment) A7<-kruskal.test(X7~treatment)