similar to: cor.test observations limit

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

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 =

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",

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.

Dear colleagues, I teach statistics using SPSS. I want to use R instead. I hit on one problem and I need some quick advice. When I want to work with ordinal variables, in SPSS I can compute the median or create a barchart or compute a spearman correlation with no problems. In R, if I "read" the ordinal variable as numeric, then I cannot do a barplot because I miss the category names. If

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

Dear all, I am trying to compute a matrix of Pearson's `r' or Spearman's `rho' rank correlation coefficients using rcorr (Hmisc) the following way: > mx<-rcorr(x, type="spearman")[1] but then ... > is.matrix(mx) [1] FALSE Even if I use as.matrix the result is not better. What can I do? Thank you all Luca

Dear list, I get the following message when I use rcorr in library "Hmisc" ------------------------------------------------------ > rcorr(lskPox0t30, type=c("spearman")) Error in "[<-.data.frame"(*tmp*, is.na(x), value = 1e+30) : matrix subscripts not allowed in replacement ------------------------------------------------------ I do not understand

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

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)

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

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",

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): >

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

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

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

Hello, Is there a way to extract output objects from a stats test without viewing the entire output? I am trying to do so in the following: define a vector of length j for( i in 1: length (vector)) { vector[i] = cor.test (datavector1, datavector2[i], method=("spearman")) } I would like the reported Spearman's rho to be saved in a vector. I have tried a few different ways of