rcorr Computes a matrix of Pearson's r or Spearman's
rho rank correlation coefficients for all possible pairs of
columns of a matrix. Missing values are deleted in pairs rather than
deleting all rows of x having any missing variables. Ranks are
computed using efficient algorithms (see reference 2), using midranks
for ties.

Usage

rcorr(x, y, type=c("pearson","spearman"))

# S3 method for rcorr
print(x, …)

Arguments

x

a numeric matrix with at least 5 rows and at least 2 columns (if
y is absent). For print, x is an object
produced by rcorr.

y

a numeric vector or matrix which will be concatenated to x. If
y is omitted for rcorr, x must be a matrix.

type

specifies the type of correlations to compute. Spearman correlations
are the Pearson linear correlations computed on the ranks of non-missing
elements, using midranks for ties.

…

argument for method compatiblity.

Value

rcorr returns a list with elements r, the
matrix of correlations, n the
matrix of number of observations used in analyzing each pair of variables,
and P, the asymptotic P-values.
Pairs with fewer than 2 non-missing values have the r values set to NA.
The diagonals of n are the number of non-NAs for the single variable
corresponding to that row and column.

Details

Uses midranks in case of ties, as described by Hollander and Wolfe.
P-values are approximated by using the t or F distributions.

References

Hollander M. and Wolfe D.A. (1973). Nonparametric Statistical Methods.
New York: Wiley.

Press WH, Flannery BP, Teukolsky SA, Vetterling, WT (1988): Numerical
Recipes in C. Cambridge: Cambridge University Press.