similar to: Kruskal Walllis test

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 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

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

typically, the apply family wants you to use vectors to run functions on. However, I have a function, kruskal.test, that requires 2 arguments. kruskal.test(Herb.df$Score,Herb.df$Year) This easily computes the KW ANOVA statistic for any difference across years.... However, my data has multiple sites on which KW needs to be run... here's the data: Herb.df<-

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 think I am right in saying that a 2 sample wilcox.test is equal to a 2 sample kruskal.test and a 2 sample t.test is equal to a 2 sample anova. This is also stated in the ?kruskal.test man page: The Wilcoxon rank sum test (wilcox.test) as the special case for two samples; lm together with anova for performing one-way location analysis under normality assumptions; with Student's t

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)

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, ?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 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

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 >>

I submit a couple options for addressing bug 16719: kruskal.test documentation for formula. https://bugs.r-project.org/bugzilla3/show_bug.cgi?id=16719 disallow-character.diff changes the documentation and error message to indicate that factors are accepted. allow-character.diff changes the kruskal.test functions to convert character vectors to factors; documentation is updated accordingly. I

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]

Hi I need to test scores from questionnaires ADDQoL by age group by Kruskal test. But he wrote me: kruskal.test (wis1 ~ vekkat) Error in kruskal.test.default (c (-2, -4, 0, -1, -1, -3, 0, -4, 0, -1, 0,: all group levels must be finite Vekkat is as.factor and wis1 is as.nuemric How to remove this error? Please advise me. Thank you [[alternative HTML version deleted]]

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)

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

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

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

Hi, Please dput() your example dataset. dat1<- read.table(text="a?? a?? a?? a??? a??? b?? b??? b??? c??? c?? c??? c 2? 4??? 5?? 2??? 7??? 2?? 2??? 6??? 3??? 7?? 9??? 3 3? 3?? 4?? 1???? 6??? 8?? 1??? 3??? 5??? 2??? 6??? 3",sep="",header=FALSE,stringsAsFactors=FALSE) library(reshape) ?dat2<-melt(as.data.frame(t(dat1)),id.var="V1")[,-2]

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