similar to: Rank sum in friedman test

Dear all, I'm using friedman rank test in R. I need to know which P value is used default and procedure to change the threshold P value. With regards jeevitesh

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

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

My data looks like this: (treatments) T1 T2 T3 DK 8 5 3 JP 5 4 1 AS 9 7 4 MK 8 4 4 DK, JP, AS, and MK are 4 different people (blocks) I am using. This is my code

Does anyone know why the two rank functions gives different results? I need to use the rank function in a "for" loop, so the sequence to be ranked is given values in the form of part (1). How can I use assignment like in part (1) to get correct ranks as in part (2)? Thank You Part (1) i<-1.94 b<-0.95-i c<-1.73-i d<-2.62-i y<-c(0.68,0.95,b,c,d) y 0.68 0.95 -0.99

Hi guys,   I have two data sets of prices: endprice0, endprice1   I use the Wilcox test:   wilcox.test(endprice0, endprice1, paired = TRUE, alternative = "two.sided",  conf.int = T, conf.level = 0.9)   The result is with V = 1819, p-value = 0.8812.   Then I calculated the z-value of the test: z-value = -2.661263. The corresponding p-value is: p-value = 0.003892, which is different from

>From the following: basin.map <- readAsciiGrid("c:/temp/area.asc", colname="area") I have a SpatialGridDataFrame which has the x and y cordinate of a cell, and the drainage area of that cell. There are many cells with a low drainage area (in my case, 33000 with an area of 37.16) and one cell with the highest drainage area (again, in my case, a drainage area of of

Hi All, I want to give ranks to elements in a column so I used: total_list$field1.rank <- rank(total_list$field1,ties.method="min") But this gives me the rank in increasing order. How do I get the ranks in decreasing order? I know decreasing = FALSE is not a legal argument here. Thanks. Jiong The email message (and any attachments) is for the sole use of the intended recipient(s)

Hi All, I had 12766 elements in a column, 12566 are values and 200 are "NA"s. I used the following line to get the ranks: total_list$MB.rank <- rank(-total_list$MB,ties.method="min",na.last=NA) but I got an error message: Error in `$<-.data.frame`(`*tmp*`, "BCRP_PW_F.rank", value = c(3949, 6182, : replacement has 12199 rows, data has 12766 What

Hello, I am trying to get the 'rank' function to work for me, but not sure what I am doing wrong. Please help. I ran the following commands: data = read.table("test1.csv", head=T, as.is=T, na.string=".", row.nam=NULL) X1 = as.factor(data[[3]]) X2 = as.factor(data[[4]]) X3 = as.factor(data[[5]]) Y = data[[2]] model = lm(Y ~ X1*X2*X3, na.action = na.exclude) fmodel =

Hi, Is there a function like rank but that solves the ties by randomly assigning a value (doesn't average ranks of ties). This is what I actually need: I want to make NA all elements of each column in an array that are ranked in a position larger that rankmax for each column. # Say I've got an array b: b<-cbind(c(1:5,5:1),c(1,12,14,2,5,4:8)) #> b # [,1] [,2] #[1,] 1 1

I"ve got a data frame with a selection of columns I want to compute a rank-order correlation matrix from without disturbing the original data frame. foo[,c("a","b","d","f","g")] What I wanted to do, intuitively, was: > cor(rank(foo[,c("a","b","d","f","g")])) but rank in that context

If you enter the following values for x and y: x: 2.2 3.7 2.1 0.4 2.8 0.3 0.4 1.4 5.4 6.0 y: 6.0 8.1 1.8 1.3 5.2 0.6 1.0 1.9 6.8 6.5 and do rank(abs(y-x)), you should get two ties, one at 0.3 and one at 0.5. R, and S-Plus5 by that matter recognise the tie at 0.5 and give it rank 3.5, but gives one of the two 0.3 values rank 1 and one of them 2, whereas they should boh be 1.5. Any suggestions? when

Hello Everyone,   I'm trying to conduct a couple of power analyses and was hoping someone might be able to help. I want to estimate the sample size that would be necessary to adequately power a couple of non-inferiority tests. The first would be a log-rank test and the second would be a Wilcoxon rank-sum test. I want to be able to determine the sample size that would be necessary to test for a

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

I have to start by saying that I am new to R, so I might miss something crucial here. It seems to me that the results of friedman.test and ks.test are "wrong". Now, obviously, the first thing which crossed my mind was "it can't be, this is a package used by so many, someone should have observed", but I can't figure out what it might be. Problem: let's start with

Dear, I'm using R software to evaluate Wilcoxon Rank Sum Test and I' getting one Warning message as this: > C1dea_com [1] 1.000 0.345 0.200 0.208 0.508 0.480 0.545 0.563 0.451 0.683 0.380 0.913 1.000 0.506 > C1dea_sem [1] 1.000 0.665 0.284 0.394 0.509 0.721 0.545 0.898 0.744 0.683 0.382 0.913 1.000 0.970 > wilcox.test(C1dea_sem,C1dea_com, paired = TRUE, alternative =

Hi everyone! I need to perform a Wilcoxon rank sum test, but I have some ties and the groups have different size also. When I deal with ties I use the wilcox.exact function, how can I solve the different size problem using this function? thanks net -- View this message in context: http://r.789695.n4.nabble.com/Wilcoxon-rank-sum-in-unbalanced-design-tp3447400p3447400.html Sent from the R help

Full_Name: Stella David Version: 2.1.0 OS: mingw32 Submission from: (NULL) (137.250.161.136) It seems that rank doesn't work right on vectors containing negative values. If the negative value is the first component or there are only two components, it works, but if the negative value is somewhere in the middle there's a problem. Here are my examples: > # wrong: > x<-

SAS proc rank has ties options of high and low that would allow producing ranks of the type found in the sports pages, e.g., rank (c(1,1,2,2,2,2,3)) == 1 1 3 3 3 3 7 Could R support these ties.methods?