similar to: 2 sample wilcox.test != kruskal.test

Hi, I am trying to do a kruskal wallis test on two lists, fVisited and cSN: fVisited[[1]] [1] 0.17097623 0.30376141 0.17577266 0.14951855 0.03959753 0.08096217 0.05744888 0.02196257.... .... cSN[[1]] [1] 0.08557303 0.36477791 0.19601252 0.12981040 0.05351320 0.10385542 0.03539577 0.03106175.... So if I just want to do a test on just one of the entries this is simple enough:

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 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, ?kruskal.test() ?a<- c(2,4,5,2,7) ?b<- c(2,2,6) ?c<- c(3,7,9,3) ?kruskal.test(list(a,b,c)) # ?#? Kruskal-Wallis rank sum test # #data:? list(a, b, c) #Kruskal-Wallis chi-squared = 2.003, df = 2, p-value = 0.3673 A.K. Hi I need an expression in R to apply a kruskal.test to this data (for example). a ? a ? a ? a ? ?a ? ?b ? b ? ?b ? ?c ? ?c ? c ? ?c 2 ?4 ? ?5 ? 2 ? ?7 ? ?2 ? 2 ?

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

Hello, I am running Kruskal-Walis test in R. When I try to save results using write.table it gives me the following error : Error in as.data.frame.default(x[[i]], optional = TRUE, stringsAsFactors = stringsAsFactors) : cannot coerce class "htest" into a data.frame The overall code is as follows : >data_file = read.table("~/DATA.dir/data_file.txt", header=T)

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]

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, 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

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

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

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)

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

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

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

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

Hi, i have a question in R, How and what command you need to do to run a kruskal-wallis test without the built in command 'kruskal.test'? many thanks. _________________________________________________________________ [[alternative HTML version deleted]]

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

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

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