similar to: wilcox.test, CI (PR#3666)

Full_Name: Patrick Hodgson Version: 2.0 OS: solaris 2.9 Submission from: (NULL) (65.94.128.161) The value reported for the parameter W in the function wilcox.exact appears to be incorrect. I have checked the reference in the help file for this function (Myles & Hollander 1973, as well as 2nd ed. 1999 by same authors) and it is clear that W is the sum of the ranks of the data set with the

This is my first post to the mailing list and I guess it's a pretty stupid question but I can't figure it out. I hope this is the right forum for these kind of questions. Before I started using R I was using STATA to run a Wilcoxon signed-rank test on two variables. See data below:

Does anyone know why wilcox.exact gives W-statistic 6 instead of 12 as indicated below. 12 is the rank sum of group 0 of x, which is the linear statistic computed by wilcox_test. y<-c(1,2,3,4,5) x<-c(1,1,0,0,0) (a) wilcox.exact wilcox.exact(y~x) Exact Wilcoxon rank sum test data: y by x W = 6, p-value = 0.2 alternative hypothesis: true mu is not equal to 0 (b) wilcox_test

hi, i am looking for a way to correct for ties in the wilcoxon signed rank test -> e.g. wilcox.test(x,mu=.5) one way i have heard of is to look up the p value in a table that has been produced by Buck (1975). obviously i need to know the T-value to do that -> how do i get the T-value from the wilcox.test() function. is there any other (already implemented) way to correct for ties in

Hello, Writing to share some things I've found about wilcox.test() that seem a a bit inconsistent. 1. Inf values are not removed if paired=TRUE # returns different results (Inf is removed): wilcox.test(c(1,2,3,4), c(0,9,8,7)) wilcox.test(c(1,2,3,4), c(0,9,8,Inf)) # returns the same result (Inf is left as value with highest rank): wilcox.test(c(1,2,3,4), c(0,9,8,7), paired=TRUE)

The point estimates produced by wilcox.test are perverse (not wrong, just brain damaged). The Hodges-Lehmann estimator that goes with the signed rank test is the median of the Walsh averages. The Hodges-Lehmann estimator that goes with the rank sum test is the median of the pairwise differences. wilcox.test agrees except that it uses the following very peculiar definition of "sample

Dear R friends, here I write again about the wilcox.exact() problem. I want to compare two sets of categorical data, and in one case it says "negative length vectors not allowed", and in the other one I get the error "cannot allocate vector of length ...". On http://rapidshare.com/files/298621893/wilcox.exact_trouble.Rdata.html you can download the data that cause the

I get these BIZARRE results from wilcox.test() When INCREASING the number of samples i get INCREASED p-values. When increasing the number of samples further, the p-values goes down again. This seems really bizarre! Can anyone explain why this is so?! Example: > w <- wilcox.test(c(1:40),(c(1:40)+100)) > w$p.value [1] 1.860340e-23 > w <- wilcox.test(c(1:50),(c(1:50)+100)) >

Dear All, I have two simple data samples (no groups or factors, etc.) and would just like to compute the two-sample Wilcoxon Rank Sum test using the wilcox_test function contained in the coin package, which is reportedly better than the regular wilcox.test function because it performs some adjustment for ties. Would anyone know how to craft a script to perform this task? Much appreciated. Janh

I'm working on a quick tutorial for my students, and was planning on using Mann-Whitney U as one of the tests. I have the following (fake) data grade <- c("MVG", "VG", "VG", "G", "MVG", "G", "VG", "G", "VG") sex <- c( "male", "male", "female", "male",

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Hi, In the exactRankTest package, I've become aware that you can get anomalous p-values (i.e., above 1) from the wilcox.exact method, as in: > wilcox.exact(c(-0.6,0.8,-0.5)) Exact Wilcoxon signed rank test data: c(-0.6, 0.8, -0.5) V = 3, p-value = 1.25 alternative hypothesis: true mu is not equal to 0 This is disturbing. Has anyone encountered this before, and if so

I have a question concerning the Wilcoxon signed-rank test, and specifically, which R subroutine I should use for my particular dataset. There are three different commands in R (that I'm aware of) that calculate the Wilcoxon signed-rank test; wilcox.test, wilcox.exact, and wilcoxsign_test. When I run the three commands on the same dataset, I get different p-values. I'm hoping that

Thank you for a fast response. Nice to see this mailing list being so alive. Regarding Inf issue: I agree with your assessment that Inf should not be removed. The code gave me an impression that Inf values were intentionally removed (since is.finite() was used everywhere, except for paired case). I will try to adjust my patch according to your feedback. One more thing: it seems like you

Hi there, I am trying to do multiple pairwise Wilcoxon signed rank tests in a manner similar to: a <- c(runif(1000, min=1,max=50), rnorm(1000, 50), rnorm(1000, 49.9, 0.5), rgeom(1000, 0.5)) b <- c(rep("group_a", 1000), rep("group_b", 1000), rep("group_c", 1000), rep("group_d", 1000)) pairwise.wilcox.test(a, b, alternative="two.sided",

Dear R friends, I want to compare two datasets and I get the message Error in .Call("cpermdist2", ma = as.integer(m), mb = as.integer(col), : negative length vectors are not allowed after specifying the exact test. I'm using the exactRankTests package. Do you suggest me using the coin library, or is there anything "wrong" with my data? Kind regards, David --

I've got two set of data : 22.45 21.56 20.48 19.59 21.52 = A and 22.15 21.98 20.42 20.58 19.61 = B I perform a wilcox.test on this two set wilcox.test(A, B) and I'd this answer: Wilcoxon rank sum test data: A and B W = 12, p-value = 1 alternative hypothesis: true mu is not equal to 0 Should I interpret that there is no difference between the two sets ? -- Cordialement

Dear List, after updating the exactRanksumTests package I receive a warning that the package is not developed any further and that one should consider the coin package. I don't find the signed rank test in the coin package, only the Wilcoxon Mann Whitney U-Test. I only found a signed rank test in the stats package (wilcox.test) which is able to calculate the exact pvalues but unfortunately

does anybody know why there are the two warnings in the example above? Regards Knut > day_4 [1] 540 1 1 1 1 1 1 300 720 480 > day_1 [1] 438 343 1 475 1 562 500 435 1045 890 > is.vector (day_1) [1] TRUE > is.vector (day_4) [1] TRUE > wilcox.test(day_4 ,day_1,paired=TRUE,alternative="two.sided",exact=TRUE,conf.int=TRUE) Wilcoxon

Dear all, When we perform a Wilcoxon rank sum test (on two samples with different sizes) we get a test statistic. My question is, as the value of test statistic increases the difference between the distributions of the two samples also increase, right? Thanks in advance, João Fadista [[alternative HTML version deleted]]