similar to: bug in cor.test(method = "spearman")

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:

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 =

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

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,

Full_Name: Ian Wilson Version: R-1.8.0 OS: Windows (but own compilation) Submission from: (NULL) (139.133.7.38) the p-value is incorrect for cor.test using method "spearman" in R-1.8.0. This was not the case in R-1.7.1. Version R-1.8.0 on Windows > cor.test(rnorm(50),rnorm(50),method="spearman") Spearman's rank correlation rho data: rnorm(50) and rnorm(50) S

Hello, Does anyone know if the cor function, when method = "spearman", returns a correlation coefficient corrected for any ties in the ranks of the data? I have data with quite a few ties and am thinking that I should use a calculation of the coefficient corrected for ties, but before I try and code this calculation myself, I thought I should check whether or not cor() automatically

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,

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

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

> version _ platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status major 1 minor 8.1 year 2003 month 11 day 21 language R > cor( 1:3, rep(NA,3) ) # OK Error in cor(1:3, rep(NA, 3)) :

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, 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): >

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 everyone, I'm sorry if this turns out to be more a statistical question than one specifically about R - but would greatly appreciate your advice anyway. I've been using a logistic regression model to look at the relationship between a binary outcome (say, the odds of picking n white balls from a bag containing m balls in total) and a variety of other binary parameters:

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

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))

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 =

Full_Name: Petr Savicky Version: 2.7.2, 2.8.1, 2.9.0 OS: Linux Submission from: (NULL) (147.231.6.9) The p-value of Spearman's rank correlation test is calculated in cor.test(x, y, method="spearman") using algorithm AS 89. However, the way how AS 89 is used incures error, which may be an order of magnitude larger than the error of the original algorithm. The paper, which

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, I have just encountered a strange behaviour from 'cor' with regards to the treatment of NAs when calculating Spearman correlations. I guess it is a subtle bug. If I understand the help page correctly, the two modes 'complete.obs' and 'pairwise.complete.obs' specify how to deal with correlation coefficients when calculating a correlation _matrix_. When calculating