similar to: Rank /core test simulation

Hi all, I am a biostatistician and I have developed my own ranking system for clinical data. I would like to test the efficiency of it w.r.t. to other ranking systems. I would like to simulate the data and after assigning ranks to my observed scores(after neglecting dropouts), observe the type I error. If I want to do a Kruuskal Wallis type of test, what test statistic should I use to test for a

Hi all, I am a biostatistician and I have developed my own ranking system for clinical data. I would like to test the efficiency of it w.r.t. to other ranking systems. I would like to simulate the data and after assigning ranks to my observed scores(after neglecting dropouts), observe the type I error. If I want to do a Kruuskal Wallis type of test, what test statistic should I use to test for a

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

how do I check the rank of a matrix ? say A= 1 0 0 0 1 0 then rank(A)=2 what is this function? thanks I did try help.search("rank"), but all the returned help information seem irrelevant to what I want. I would like to know how people search for help information like this. rank(base) Sample Ranks SignRank(stats) Distribution of the

Hi, Is anyone aware of a rank-based, non-paired test such as the Krustal-Wallis, that can accommodate weights? Alternatively, would it make sense to simulate a dataset by duplicating observations in proportion to their weight, and then using the Krustal-Wallis test? thanks! Dylan

Hello! I need to use Kruskal-Wallis test and post-hoc test (Dunn's test) for my data. But when I searched around, I only found this function: kruskal.test. But nothing for Dunn's test. So I started to write one myself. But I do not know how to count ties in the data frame. I can use for loops but it seems long and unnecessary since the rank function actually knows the ties. So

Hello all, Here goes one of my first functions. I want to make a nonparametric multiple sample comparison with unequal sample sizes (see Zar?s Biostatistical Analysis, 3rd. Ed., pg. 201 Example 10.11, pg. 288 Example 11.10). In the real world, I want to compare samples of fish length captured with different fishing gears. After using the Kruskal-Wallis test I want to check the differences

This is more of a conceptual/methodological question than "how to do it in R", so anyone who cares to reply might want to do it off list. I have censored rank order data .. electors have been asked to rank the 4 most important issues out of a list of 20. For each individual we therefore have a vector of 20 measurements 1..5, where 1..4 are ranks and 5 = not ranked/less important than

Hello, What is the best way to get ranks for a vector of values, limit the range of rank values and create equal count in each group? I call this uniform ranking...uniform count/number in each group. Here is an example using three groups: Say I have values: x = c(3, 2, -3, 1, 0, 5, 10, 30, -1, 4) names(x) = letters[1:10] > x a b c d e f g h i j 3 2 -3 1 0 5 10 30 -1 4 I

Dear fellow R users, Keywords: Kruskal-Wallis, Post-Hoc, pair-wise comparisons, Nemenyi-Damico-Wolfe-Dunn test, coin package, oneway_test I am using the "oneway_test" function in the R package "coin" and I am obtaining results which I cannot believe are accurate. I do not wish to waste anyone's time and so if the following problem is rather trivial, I apologize, however I

Hi, I am running the following example which can be found on page 12 of the pdf file of COIN package wt<-wilcox_test(pd~age,data=water_transfer,distribution="exact", conf.int=TRUE) "wt" actually contains the estimate of difference in location and the confidence interval of it. I am just wondering how can I extract these values? From the examples, I understand that the

Hello List, I'm trying to prepare some lecture notes on non parametric methods, and I can't manually reproduce the results of the wilcox.test function for ordinal data. The data I'm using are from David Howell's website, available here http://www.uvm.edu/~dhowell/StatPages/More_Stuff/OrdinalChisq/OrdinalChiSq.html If I run the wilcox.test function on the data I get a p-value of

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

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

I think I've gotten my Emacs/Sweave/R system set up correctly, thanks to Vincent and Jim, but I haven't been successful getting my first document produced. I'm trying to use one of Friedrich Leisch's examples, http://www.ci.tuwien.ac.at/~leisch/Sweave/example-1.Snw. I cut and pasted the text into a document sweaveexample.Rnw in Emacs. It seemed to be processed successfully with R:

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]

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

Hello, I have an experimental design where I would like to use separate ranking events to predict an independent ranking event. I have been using function clmm in the ordinal library but now realize that I am violating one of the assumptions. I have included a subset of the data. I am looking at how undergraduate students perceive the architecture and biological correctness of box and arrow

Hi list, 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 (kruskal.test() function object). I was looking for something like the Dunn Test. I’ve searched the internet but nothing seemed to define a way to it. Do You have any suggestion? Other equivalent test maybe! Thanks in

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: