similar to: Multiple output from cor.test

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

Full_Name: Rob Baer Version: 2.0.0 OS: Windows Submission from: (NULL) (198.209.172.106) Request/wish summary: state the alternative hypothesis before the t-test and p-value A typical cor.test output looks like the following: > x=runif(30)*10 > y=runif(30)*10 > cor.test(x,y) Pearson's product-moment correlation data: x and y t = 0.6161, df = 28, p-value = 0.5428

Hi, I am trying to use R for some survey analysis, and need to compute the significance of some correlations. I read the man pages for cor and cor.test, but I am confused about - whether these functions are intended to work the same way - about how these functions handle NA values - whether cor.test supports 'use = complete.obs'. Some example output may explain why I am confused:

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

Hello everyone, I'm a new R user switching from SAS and JMP. In the first few days, I have been trying to do a fairly simple task but yet found no success. I've checked the help archive as well as few R textbooks but didn't seem to find the answer. So, please help me if you can. Basically, I want to calculate the correlation between variable A and B for every subject in my

Hi, I've got 4 variables that I want to effectively 'stack' so that I have a grand R variable and a grand L variable. This works to achieve that goal: Twin1cor<-with(twin.wide,cbind(ACDepthR.1,ACDepthL.1)) Twin2cor<-with(twin.wide,cbind(ACDepthR.2,ACDepthL.2)) Both<-rbind(Twin1cor,Twin2cor) > str(Both) num [1:1858, 1:2] 3.36 NA NA NA NA NA NA 3.92 3.5 NA ... - attr(*,

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

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

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

Hello all, I'm a new user of R, experienced with Octave/MATLAB and therefore struggling a bit with the new syntax. One of the easy things in Octave or MATLAB is to plot multiple lines or sets of points by using a matrix where either the columns or the rows contain the y-values to be plotted. Both packages automatically give each line/points their own unique colour, character etc. I'm

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,

I'm calculating correlations between two matrices mat1 <- matrix(sample(1:500,25), ncol = 5, dimnames=list(paste("mat1row", 1:5, sep=""), paste("mat1col", 1:5, sep=""))) mat2 <- matrix(sample(501:1000,25), ncol = 5, dimnames=list(paste("mat2row", 1:5, sep=""), paste("mat2col", 1:5, sep="")))

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

Dear all How does print.htest display the p-value in scientific notation? > (x <- cor.test(iris[[1]], iris[[3]])) Pearson's product-moment correlation data: iris[[1]] and iris[[3]] t = 21.65, df = 148, p-value < 2.2e-16 alternative hypothesis: true correlation is not equal to 0 95 percent confidence interval: 0.8270 0.9055 sample estimates: cor 0.8718 Above the p-value comes

Hi again, I've got few very good options from the list and since they were not posted to the list, I will provide a summary. Thank you very much to all who answered and I hope this summary will benefit others interested in solving similar problems like that. Yasir Kaheil re-wrote my original code in a more streamlined way: pr<-array(0,c(dim(x)[2],dim(x)[2])); for (i in 1:dim(x)[2]) for

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 want to give the "rho" value below to another variable.How ? > Spearman's rank correlation rho > > > > data: a[, 3] and a[, 2] > > S = 22, p-value = 0.001174 > > alternative hypothesis: true rho is not equal to 0 > > sample estimates: > > rho > > 0.8666667 -- View this message in context:

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:

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",

Friends I am new to R (and statistics) so am struggling a bit. Briefly... I am interested in getting the P-Value from cor(X) where X is a matrix. I have found cor.test. Verbosely... I have 4 vectors and can generate the corellation matrix... > cor(cbind(X1, X2, X3, X4)) X1 X2 X3 X4 X1 1.00000000 -0.06190365 -0.156972795 0.182547517 X2