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Exploring correlations with R using cor.prob and chart.Correlation
## Correlation matrix with p-values. See for documentation of this function
cor.prob <- function (X, dfr = nrow(X) - 2) {
R <- cor(X, use="pairwise.complete.obs")
above <- row(R) < col(R)
r2 <- R[above]^2
Fstat <- r2 * dfr/(1 - r2)
R[above] <- 1 - pf(Fstat, 1, dfr)
R[row(R) == col(R)] <- NA
## Use this to dump the cor.prob output to a 4 column matrix
## with row/column indices, correlation, and p-value.
## See StackOverflow question:
flattenSquareMatrix <- function(m) {
if( (class(m) != "matrix") | (nrow(m) != ncol(m))) stop("Must be a square matrix.")
if(!identical(rownames(m), colnames(m))) stop("Row and column names must be equal.")
ut <- upper.tri(m)
data.frame(i = rownames(m)[row(m)[ut]],
j = rownames(m)[col(m)[ut]],
# get some data from the mtcars built-in dataset
mydata <- mtcars[, c(1,3,4,5,6)]
# correlation matrix
# correlation matrix with p-values
# "flatten" that table
# plot the data

I would to cite this functions in a scientific paper.
I tried to use the function 'citation' but it didn't work well.

very helpful. thanks!

need to correct p-values for multiple comparison.

iveksl2 commented Mar 25, 2016

Nice, you should put these functions into an R-Package! Thx

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