similar to: cor() function, method="spearman"

Dear HelpeRs, I have some data: "ice" <- structure(c(0.386, 0.374, 0.393, 0.425, 0.406, 0.344, 0.327, 0.288, 0.269, 0.256, 0.286, 0.298, 0.329, 0.318, 0.381, 0.381, 0.47, 0.443, 0.386, 0.342, 0.319, 0.307, 0.284, 0.326, 0.309, 0.359, 0.376, 0.416, 0.437, 0.548, 41, 56, 63, 68, 69, 65, 61, 47, 32, 24, 28, 26, 32, 40, 55, 63, 72, 72, 67, 60, 44, 40, 32, 27, 28, 33,

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))

Hallo! Is there an error in cor to calculate Spearman correlation with cor if there are NA's? cor.test gives the correct result. At least there is a difference. Or am I doing something wrong??? Does anybody know something about this? a<-c(2,4,3,NA) b<-c(4,1,2,3) cor(a, b, method="spearman", use="complete.obs") # -0.9819805 cor.test(a, b,

Greetings. There seems to be a problem with the P-value computation in the cor.test with method="spearman". In R1.8.0 (MS Windows) I seem to be getting intermittently nonsense P-values, but the rho's are OK. I can get this reproducibly with the toy example attached where the first use is OK and subsequent calls with the same data give nonsense. (I have also seen the problem

Hi. I am currently trying to run some Spearman correlations, and have encountered two issues. 1) When using cor.test() with a variable that includes ties, I get the "Cannot compute exact p-values with ties" error. I have read that this function now uses an asymptotic formula that allows for ties, so do not understand why I am getting this error. (I am running version 2.4.0.) I

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, I have the following two measurements stored in mat: > print(mat) [,1] [,2] [1,] -14.80976 -265.786 [2,] -14.92417 -54.724 [3,] -13.92087 -58.912 [4,] -9.11503 -115.580 [5,] -17.05970 -278.749 [6,] -25.23313 -219.513 [7,] -19.62465 -497.873 [8,] -13.92087 -659.486 [9,] -14.24629 -131.680 [10,] -20.81758 -604.961 [11,] -15.32194 -18.735 To calculate the ranking

I posted this on R help, and a few others responded indicating they too were able to replicate the error as a function of missing data. I believe this should not be the case and hence and reporting it here. ### Code provided on R-Help by Ivar Herfindal # Simulate data testdata <- cbind.data.frame(gr=3Drep(letters[1:4], each=3D5), = aa=3Drnorm(20), bb=3Drnorm(20)) # Introduce some missingness

Hi all, I am trying to figure out the formula used by R's Spearman rho (using cor(method="spearman")) because I can't seem to get the same value as by calculating "by hand". Perhaps I'm using "cor" wrong, but I don't know where. Basically, I am running these commands: > y=read.table(file="tmp",header=TRUE,sep="\t") >

Hi R specialists, When testing the association between two time series the cor.test gives the following message...-> p-values may be incorrect due to tie What does it mean? (it is not described in the help) Thankx, Jan > cor.test(Origi[,1],Origi[,2], alternative = c("two.sided"),method = c("spearman"), conf.level = 0.95) Spearman's rank correlation rho

Hi, Does anyone know if the cor() function under the stats package adjusts for ties? Specifically, with method="spearman" does R compute the ties adjusted version of Sperman's rank correlation coefficient or the uncorrected version? If not, does anyone know of a function/package that will do this? Thanks! Courtney M.

Hi, How can I make the cor(x, y, method="spearman") call to produce an error when the input to it (x, y) produces an error? Here is a simple example: > a <- c(0, 1, 2) > b <- c(100, 2, 4) ## error: > log(a) [1] -Inf 0.0000000 0.6931472 ## error, as expected: > cor(log(a), log(b), method="pearson") [1] NaN ## not an error any more (not expected): >

Pardon my ignorance, but is there a difference in cor.test between exact=FALSE and exact=NULL when method=spearman? Take for example: x<-c(1,2,2,3,4,5) y<-c(1,2,2,10,11,12) cor.test(x,y, method="spearman", exact=NULL) This gives an error message, Warning message: Cannot compute exact p-values with ties in: cor.test.default(x, y, method = "spearman", exact = NULL)

Dear R maintainers, R is great. Now that I have that out of the way, I believe I have encountered a bug, or at least an inconsistency, in how Spearman and Kendall rank correlations are handled. Specifically, cor() and cor.test() do not produce the same answer when the data contain NAs. cor() treats the NAs as data, while cor.test() eliminates them. The option use="complete.obs" has

Colleagues, I ran some nonparametric regressions in R (run in RedHat Linux), then a colleague repeated the analyses in SAS. When we obtained different results, I tested S-Plus (same Linux box). And, got yet different results. I replicated the results with a small dataset: DATA: 37.5 23 37.5 13 25 16 25 12 100 15 12.5 19 50 20 100 13 100 10 100 10 100 16 50 10 87.5

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, all. Yet another beginner to R : ) I wonder, how it's possible to get the value of a coefficient from the object produced by cor.test() ? > cor.test(a, b, method="spearman") Spearman's rank correlation rho data: a and b S = 21554.28, p-value = 2.496e-11 alternative hypothesis: true rho is not equal to 0 sample estimates: rho 0.6807955 Warning message: In

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

Arrrrr, I think I've found a bug in the behavior of the stats::cor function when NAs are present, but in case I'm missing something, could you look over this example and let me know what you think: > a = c(1,3,NA,1,2) > b = c(1,2,1,1,4) > cor(a,b,method="spearman", use="complete.obs") [1] 0.8164966 > cor(a,b,method="spearman",

I would like to turn off the warnings from cor.test while retaining exact=NULL. Is that possible ? > cor.test(c(1,2,3,3,4,5), c(1,2,3,3,4,5), method = "spearman") Spearman's rank correlation rho data: c(1, 2, 3, 3, 4, 5) and c(1, 2, 3, 3, 4, 5) S = 0, p-value < 2.2e-16 alternative hypothesis: true rho is not equal to 0 sample estimates: rho 1 Warning message: In