similar to: Paired Weighted Wilcoxon test in R

Hi DC9, As no one has answered, I would say that as both the survey package and Professor Lumley are widely respected, that is as good as it gets. Jim On Fri, Jun 23, 2017 at 7:26 PM, Dreams Collector <dreamscollector9 at gmail.com> wrote: > Dear R-users, > > I?m trying to perform a non-parametric statistical pairwise comparison of two samples "x" and "y" using

Given this example #start code a<-c(0,70,50,100,70,650,1300,6900,1780,4930,1120,700,190,940, 760,100,300,36270,5610,249680,1760,4040,164890,17230,75140,1870,22380,5890,2430) b<-c(0,0,10,30,50,440,1000,140,70,90,60,60,20,90,180,30,90, 3220,490,20790,290,740,5350,940,3910,0,640,850,260) wilcox.test(a, b, paired=FALSE) #sum of rank for first sample sum.rank.a <-

Hello everyone, I'm having some trouble interpreting the results of a Wilcoxon (Mann-Whitney U) test. Hope you can help. This is the R script that I am running: a <- c(1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 2, 1, 5, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 3, 1, 1) b <- c(1, 2, 1, 1, 2, 3, 2, 2, 1, 2, 1, 1, 1, 2) wilcox.test(a, b, alternative="t", mu=0, exact=FALSE, paired=FALSE) #1st

An earlier post had posed the question: "Does anybody know what is relation between 'T' value calculated by 'wilcox_test' function (coin package) and more common 'W' value?" I found the question interesting and ran the commands in R and SPSS. The W reported by R did not seem to correspond to either Mann-Whitney U, Wilcoxon W or the Z which I have more

Hello, I am hoping someone could shed some light into the Wilcoxon Rank Sum Test for me? In looking through Stats references, the Mann-Whitney U-test and the Wilcoxon Rank Sum Test are statistically equivalent. When using the following dataset: m <- c(2.0863,2.1340,2.1008,1.9565,2.0413,NA,NA) f <- c(1.8938,1.9709,1.8613,2.0836,1.9485,2.0630,1.9143) and the wilcox.test command as

Hallo, is there any extension of the pairwise Wilcoxon test to a dependent samples layout with replicates (or, in other terms, a one-way layout with blocking and replicates)? The Wilcoxon method with matched pairs works for the case of dependent samples with one observation per block, while the Mann-Whitney test works for independent samples, thus one single block and replicated observations. Is

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

Hello, can someone please help me with coding a function for a bootstrap WMW test (package boot, R under Windows, version 1.6.2)?

Hello All, I am writing to ask your opinion on how to interpret this case. I have two vectors "a" and "b" that I am trying to compare. The wilcoxon test is giving me a pvalue of 5.139217e-303 of a over b with the alternative "greater". Now if I make a summary on each of them I have the following > summary(a) Min. 1st Qu. Median Mean 3rd Qu.

Probably, it's an obvious info, but I have not found anything in R FAQ concerning this feature/bug. The results of ks.test and wilcoxon.test (in the Mann-Whitney version, paired = 'FALSE') don't coincide with the results from the other statistical packages, e.g. Statistica, Medcalc, and (as for MW test) from the numerous online MW tests. E.g. Statistica p-value=0.0435353 Medcalc

Hi, R allows me to run a one sample Wilcoxon test like this: wilcox.test(c(1,3.5,2.1,4,1.5,5), mu=2, exact=TRUE) The function 'wilcoxsign_test' from the package 'coin' should (I suppose) be able to calculate exact p values even if there are ties in the ranks. However, I couldn't find information on how to run a one sample test using 'wilcoxsign_test' like in the

The function 'wilcox.test' in R and S gives (almost) identical results (see below). 'qwilcox' however, does not: > qwilcox(p,5,5) p: 0.025 0.975 -------------------- R> 3 22 S> 18 37 I originally wanted to ask a questions, but then I found the answer. Given the confusion I run into, I wonder if this experience is worth reporting. The

Dear list, Let's say I have data a=c(37.961,38.214,57.68) b=c(77.56,61.875,67.683) wilcox.test(a,b) the wilcoxon test only gives me a p value with one decimal place. Is this normal? Thanks. Jun [[alternative HTML version deleted]]

Hi. I'm going to introduce the R-package for a group of medical doctors later this week and is a little confused about there use of a test named "willcoxon-pratt" for testing if the clinical and biochemical markers has decreased significantly after the use of some drugs for a group of patients. Looking into the R-functions I would in R recommand using a matched-pairs Wilcoxon

Hello, I use t.test for normal distributed and wilcox.test for non-normal distributed samples. It is easy to write a function for t.test that calculates the effect size, because all parts of the formula are available from the t.test result: r = sqrt(t*t / (t*t + df)) However, for Wilcoxon tests, the formula for effect sizes is: r = Z / sqrt(N) I wonder how I can calculate the Z-score in R for

On 06/30/2013 02:14 AM, Anton Korobeynikov wrote: > Hi Tobi, > > First of all, all this is http://llvm.org/bugs/show_bug.cgi?id=1367 :) > >> The statistical test ministat is performing seems simple and pretty >> standard. Is there any reason we could not do something similar? Or are we >> doing it already and it just does not work as expected? > The main problem

Hi Tobi, First of all, all this is http://llvm.org/bugs/show_bug.cgi?id=1367 :) > The statistical test ministat is performing seems simple and pretty > standard. Is there any reason we could not do something similar? Or are we > doing it already and it just does not work as expected? The main problem with such sort of tests is that we cannot trust them, unless: 1. The data has the

Dear Sir, I am comparing two samples using wilcox.test in R. Literature appears to describe mann whitney u test as the most appropriate test to use on my data. is the wilcox.test function equivalent to mann-whitney u? Is there a way to gain the U-value as apposed to the W-value in R? Thank you

Hi, I would like to announce a new set of LNT -O3 performance testers. In a discussion titled "Question about results reliability in LNT infrustructure" Anton suggested that one way to get statistically reliable test results from the LNT infrastructure is to use a larger sample size (5-10) as well as a more robust statistical test (Wilcoxon/Mann-Whitney). Another requirement to

Does anyone have a piece of code or know how I can use R to generate a table of critical values for the Mann-Whitney (aka Wilcoxon Rank Sum) test. Ideally, I'd like a table that contains the critical values for any two samples of size 3 through 30. I could use Monte Carlo simulation or the normal approximation when n1 and n2 are greater than, 10, but I figured someone may know how to