Displaying 20 results from an estimated 10000 matches similar to: "Problem: using cor.test with by( )"
2004 Aug 30
1
Wrong result with cor(x, y, method="spearman", use="complete.obs") with NA's???
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,
2010 Jun 09
1
bug? in stats::cor for use=complete.obs with NAs
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",
2008 Jun 19
3
how to extract object from stats test output (cor.test)?
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
2004 Mar 03
1
cor(..., method="spearman") or cor(..., method="kendall") (PR#6641)
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
2003 Mar 05
1
cor.test in matrices
Hi,
For computing correlation among variables in a matrix, I use cor( ), but
for computing the p-values I'm using cor.test in the following way:
cor.p <- function(X)
{
res <- matrix(0, ncol(X), ncol(X))
for (i in 1:ncol(X))
for (j in 1:ncol(X)) res[i, j]<- cor.test(X[, i], X[, j])$p.value
rownames(res) <- colnames(res) <- colnames(X)
res
}
I'm just wondering if there is a
2003 Apr 24
3
Missing Value And cor() function
Hi r lovers!
I 'd like to apply the cor() function to a matrix which have some missing values
As a matter of fact and quite logically indeed it doesn't work
Is there a trick to replace the missing value by the mean of each variable or by any other relevant figures ?
Or should I apply a special derivate of the cor() function, (I don't have any idea if it exists and have some trouble to
2010 Jun 08
2
cor.test() -- how to get the value of a coefficient
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
2008 Sep 10
3
making spearman correlation cor() call fail with log(0) as input
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):
>
2009 Jul 07
1
cor vs cor.test
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:
2003 Oct 22
6
Something strange in cor.test in R-1.8.0 (PR#4718)
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
2007 Aug 23
1
in cor.test, difference between exact=FALSE and exact=NULL
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)
2012 Mar 07
2
how to see inbuilt function(cor.test) & how to get p-value from t-value(test of significance) ?
i can see source code of function
> cor
function (x, y = NULL, use = "everything", method = c("pearson",
"kendall", "spearman"))
{
na.method <- pmatch(use, c("all.obs", "complete.obs",
"pairwise.complete.obs",
"everything", "na.or.complete"))
2007 Sep 20
1
Bug with Cor(..., method='spearman") and by() (PR#9921)
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
2009 Apr 17
1
Turning off warnings from cor.test
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
2007 Jul 20
1
how to determine/assign a numeric vector to "Y" in the cor.test function for spearman's correlations?
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",
2005 Oct 09
3
cor doesn't accept na.rm? (PR#8193)
Full_Name: Paul Bailey
Version: 2.1.1
OS: OS X 10.3
Submission from: (NULL) (68.252.250.144)
?cor
[tells me that it has a na.rm variable]
> cor(frame2[1,],frame2[2,],na.rm=T)
Error in cor(frame2[1, ], frame2[2, ], na.rm = T) :
unused argument(s) (na.rm ...)
hmm.
2001 Nov 01
1
cor.test for a correlation matrix
Is there a simple way to run cor.test on for a matrix of correlations?
Of course, cor on a data frame produces a correlation matrix, but cor.test will only take two variables at a time. Is there a way to get behavior similar to that of cor with cor.test?
I suppose the programming alternative would be to run two for loops with the number of items and cor test embedded accessing the columns of
2011 May 16
2
about spearman and kendal correlation coefficient calculation in "cor"
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
2004 Apr 09
6
Incorrect handling of NA's in cor() (PR#6750)
Full_Name: Marek Ancukiewicz
Version: 1.8.1
OS: Linux
Submission from: (NULL) (132.183.12.87)
Function cor() incorrectly handles missing observation with method="spearman":
> x <- c(1,2,3,NA,5,6)
> y <- c(4,NA,2,5,1,3)
> cor(x,y,use="complete.obs",method="s")
[1] -0.1428571
>
2008 Aug 15
2
cor() btwn columns in two matrices - no complete element pairs
Hi everyone,
I'm trying to calculate correlation coefficients between corresponding
columns in two matrices with identical dimensions but different data. The
problem is that the matrices contain NAs in different locations. I am using
the following code to try to calculate correlations between complete sets of
data:
#Code start
maxcol<-ncol(mat1)
for (i in 1:maxcol)
{