similar to: Spearman's rank correlation test (PR#13574)

Hi All: help(cor.test) claims For Spearman's test, p-values are computed using algorithm AS 89. Algorithm AS 89 was introduced by the paper D. J. Best & D. E. Roberts (1975), Algorithm AS 89: The Upper Tail Probabilities of Spearman's rho. Applied Statistics, Vol. 24, No. 3, 377-379. Table 1(a) in this paper presents maximum absolute error |\Delta_m|, of the approximation for

Full_Name: Jan T. Kim Version: 2.1.0 (and better) OS: Linux Submission from: (NULL) (139.222.3.229) The p value in Spearman's test is NA if the length of x exceeds 46340, due to an integer overflow, occurring if length(n) > sqrt(2^31): > n <- 46341; > set.seed(1); > x <- runif(n); > y <- runif(n); > cor.test(x, y, method =

There is an even simpler way: someone wrote n*(n^2-1) as n*(n-1)*(n+1) and caused the problem. Your superfluous semicolons do definitely make your code harder to read. On Tue, 23 Aug 2005 jtk at cmp.uea.ac.uk wrote: > Full_Name: Jan T. Kim > Version: 2.1.0 (and better) > OS: Linux > Submission from: (NULL) (139.222.3.229) > > > The p value in Spearman's test is NA if

Hello, I wuold like to propose my modifications of the original cor.test to you : I tried to calcolate the correct p-value for Spearman and Kendall's test with ties. Let me know what you think. Thanks you for your time. Antonietta di Salvatore test <- function(x, ...) UseMethod("test") test.default <- function(x, y, alternative = c("two.sided",

cor.test and SuppDists give me different P-values for the same Spearman's rho. Which is correct, or am I doing something wrong? > x <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1) > y <- c( 2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8) > cor.test(x,y,method="spearman") Spearman's rank correlation rho data: x and y S = 48, p-value =

Full_Name: David Simcha Version: 2.10 OS: Windows XP Home Submission from: (NULL) (173.3.208.5) > a <- c(1:10) > b <- c(1:10) > cor.test(a, b, method = "spearman", alternative = "greater", exact = TRUE) Spearman's rank correlation rho data: a and b S = 0, p-value < 2.2e-16 alternative hypothesis: true rho is greater than 0 sample estimates:

Hi, R! Question1: I am trying to correlate two vectors of numbers (two columns of microarray signal values) by using the non-parametric Spearman's rank correlation coefficient rho: > cor.test(V2.Signal,V3.Signal,method="spearman") but I get the error message: Error in if (q > (n^3 - n)/6) pspearman(q - 1, n, lower.tail = FALSE) else pspearman(q, : missing value

Dear R developers: There is a possible bug in calculating the p-value for Spearman's rank correlation. Line 155 in file R-patched/src/library/stats/R/cor.test.R is as.double(round(q) + lower.tail), I think, it should be as.double(round(q) + 2*lower.tail), The reason is that round(q) is expected to be an even number (the S statistic), so the next feasible value is round(q)+2.

Hi, Is there a limit on the number of observations for using cor.test. For example, > library(ctest) > cor.test(rnorm(3000), rnorm(3000), method="spearman") Error in if (q > (n^3 - n)/6) pspearman(q - 1, n, lower.tail = FALSE) else pspearman(q, : missing value where logical needed In addition: Warning message: NAs introduced by coercion I mainly want to calculate

Hello R gurus, I want to calculate the Spearman rho between two ranked lists. I am getting results with cor.test that differ in comparison to my own spearman function: > my.spearman function(l1, l2) { if(length(l1) != length(l2)) stop("lists must have same length") r1 <- rank(l1) r2 <- rank(l2) dsq <- sapply(r1-r2,function(x) x^2) 1 - ((6 * sum(dsq))

Hi, I have a dataset with four categories of data, the number of samples are not the same in each category. I want to find the Spearaman's Rho. Let me give an example. x=(14.22770439,26.49420624,46.7277932,19.02550707,23.37379361,16.97789862,19.77100085,23.11270162,13.72929843,33.54430621,14.4756979,70.15811106,11.22789833,NA,NA,NA)

I have computed correlation coefficients for my dissertation data using Spearman's Rho with adjustments for tie scores; however, I do not have access to a way to find exact p's. I have a friend who has R but he doesn't know if it is appropriate for my analysis, given the constraint of tie scores? Can you advise me? Thanks. Michele Fagan -------------- next part -------------- An

Hello to all of you, R-expeRts! I am trying to compute the cor.test for a matrix that i labelled mydata according to mydata=read.csv... then I converted my csv file into a matrix with the mydata=as.matrix(mydata) NOW, I need to get the p-values from the correlations... I can successfully get the spearman's correlation matrix with: cor(mydata, method="s",

For the record (and as privately discussed with Brian Ripley), happens with all recent versions of R including R-devel from today: Consider a simple a.Rd file containing the lines ================== \name{a} \title{a} \value{\code{a} \code{\link[a]{a}} \pkg{a} \item{a}{a} } ================== with these lines, I get, e.g.: ================== R CMD Rdconv --type="txt" a.Rd a

Hallo, does anybody know if there is an implementation of the Spearman rank correlation in R that gives a correct (or at least 'safe') p-value in the case of ties?? I have browsed the R-help archives but I found nothing. Thanks a lot in advance for any help, Antonino Casile

Dear all, Suppose my data frame is as follows: id price distance 1 2 4 1 3 5 ... 2 4 8 2 5 9 ... n 3 7 n 8 9 I would like to calculate the rank-order correlation between price and distance for each id. cor(price,distance,method = "spearman") calculate a correlation for all. Then I tried to use apply(data,list='id',cor(price , distance , method =

Hi If I get a p-value less than 0.05 does that mean there is a significant relation between the 2 ranked lists? Sometimes I get a low correlation such as 0.3 or even 0.2 and the p-value is so low , such as 0.000001 , does that mean it is significant also? and would that be interpreted as significant low positive correlation or significant moderate positive correlation? Also,can R calculate the

hello help, i''ve searched through the manual pages and the only reference i can find to spearman rank correlation is cor.test, which only seems to give the significance value of the correlation. is there any way to get the actual value of rho? david. [[alternate HTML version deleted]]

Dear R-helpers, I would like to do a Spearman rank order test, and used the cor() function with the method "spearman". It gives me a number (correlation coefficient?) , but how can I get the p-value? Thank you for the help in advance! Regards, Anne-Katrin -- [[alternative HTML version deleted]]

Dear all, in package Hmisc `rcorr' computes a matrix of Spearman's `rho' rank correlation coefficients for all possible pairs of columns of a matrix. What if I want a matrix of rank correlation coefficients for pair of columns of two different matrices? I have the same question about distance metrics in package Vegan. The function 'vegdist' computes distance indexes for all