similar to: kruskal wallis for manova?

Hello All, I have a more statistical question, and how this is implemented in R. The problem is the following: We have 2 different solutions (samples), which are filtered and then the concentration of the filtrate is measured. We want to evaluate how the filter proces and the concentration measurement influences the detection of the difference of the two solutions and which step has which

enclosed a simple R script (and a data file, and the output) , with calls lda similar to the example with the iris data in the documentation. it is not working and i dont understand the error message. can anybody help me? i am using R 1.5.1 (2002.06.17) on debian woody stable. I would like to avoid updating now, because i want to keep the system in "stable". can somebody test, if the

enclosed a simple R script (and a data file) , with calls lda similar to the example with the iris data in the documentation. it is not working and i dont understand the error message. can anybody help me? i am using R 1.5.1 (2002.06.17) on debian woody stable. thanks -- Dr.Nicolaas Busscher Universit?t GH Kassel Nordbahnhofstrasse: 1a, D-37213 Witzenhausen Phone: 0049-(0)5542-98-1715, Fax:

I am using lme to handle repeated measurements. So far i can follow the examples from the book from pinheiro and bates. Now i get the problem , that i have "nested" repeated measuremnts, and i cant find out how to do the grouping part of the lme formula. 1.The simple problem ist that i have different Samples , from which i make repeated measurements (each sample is measured 6 times) and

As an R absolute beginner and an expert (very old) statistician and latex user, I'm interested in using R to produce AUTOMAGICALLY tables in latex format. I mean I would like to have the means to build an R procedure generating **FROM INSIDE** a table or a graph to be inserted directly into latex. I've read http://hesweb1.med.virginia.edu/biostat/s/doc/summary.pdf where the author speaks

Hi, how can I tell 'summary' to print the name of the summarised variable? This is probably an awkward newbie question but I didn't find an answer in the Docus, the FAQ and maillist archive. I want a summary for about 250 variables and realise it the following way (I know, that I shouldn't use iterations that way in R; but at the moment it's the easiest way for me):

Hi Since a stepwise procedure for variable selection (as e.g. in SPSS) for a LDA is not implemented in R and anyway I cannot be sure, that all the required assumptions for e.g. a procedure using a statistic based on wilks' lambda, hold (such as normality and variance homogeneity) I would like to ask you, what you would recommend me: shall I e.g. define a criterion such as the error-rate

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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

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

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 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 I have a dataframe of genomic positions something like below: chr start end strand 1a 2a 3a 1b 2b 3b 1c 2c 3c 1d 2d 3d chr1 201199522 201199523 - 51 62 63 46 53 58 53 78 37 27 65 62 chr1 201199584 201199585 - 42 49 35 54 62 55 43 56 26 21 64 63 chr1 201199603

1) L-moments: Does anyone know of any R code that will calculate these? (I'm aware that these can be calculated in S-Plus using the EnvironmentalStats for S-Plus module.) 2) Hosking & Wallis (1997): "Regional frequency analysis: an approach based on L-moments" Does anyone know of any code in either R or S-plus that implements the discordancy and homogeneity methods described

Dear All, I need to compare 4 groups of binary data having different sample sizes and would like to know if the non parametric Kruskal-Wallis test (kruskal.test) can be used for this purpose or not. Many Thanks, GK

Dear all Is there any way of doing a Tukey HSD post-hoc test after a Kruskal- Wallis or Friedman rank sum test (in the ctest package)? Thanks in advance, Albertus Dr. Albertus J. Smit Department of Botany University of Cape Town Private Bag Rondebosch 7700 South Africa Tel. +27 21 689 3032

Hi, I was wondering if it was possible to do the "Scheirer-Ray-Hare" extension of the Kruskal-Wallis test using R, or if it was possible to use some other non-parametric test for the following situation: I have continuous data that is grouped by 2 factor variables. I would like a non-parametric test because the group variances are not equal. I would like to look for the effects of

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