have a look also at function rcor.test() from package ltm.
Best,
Dimitris
----
Dimitris Rizopoulos
Biostatistical Centre
School of Public Health
Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
http://www.student.kuleuven.be/~m0390867/dimitris.htm
----- Original Message -----
From: "Monica Pisica" <[EMAIL PROTECTED]>
To: <r-help@r-project.org>
Sent: Thursday, May 08, 2008 9:05 PM
Subject: [R] applying cor.test to a (m, n) matrix
Hi everybody,
I would like to apply cor.test to a matrix with m rows and n columns
and get the results in a list of matrices , one matrix for p.val,
one for the statistic, one for the correlation and 2 for upper and
lower confidence intervals, something analog with cor() applied to a
matrix.
I have done my own function to get a matrix of p.values and i
suppose i can build similar functions for all the others. But i have
used for loops and i wonder if there is any way to actually use one
of the functions from the "apply" family to do this in a quicker
way.
Here is my little function:
cor.pval <- function(x, method = c("pearson", "kendal", "spearman"),
digit=8) {
n <- dim(x)[2]
pval <- matrix(paste(rep("c", n*n), seq(1,n*n), sep = ""), n, n,
byrow = T)
for (i in 1:n) {
for (j in 1:n){
pval[i, j] <- cor.test(x[,i], x[,j], method = method)$p.value
}
}
pval <- matrix(round(as.numeric(pval),digit), n, n, byrow = T)
rownames(pval) <- colnames(x)
colnames(pval) <- colnames(x)
return(pval)
}
Thanks for any input,
Monica
_________________________________________________________________
esh_messenger_052008
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