rcorr {Hmisc}  R Documentation 
Matrix of Correlations and Pvalues
Description
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 class 'rcorr'
print(x, ...)
Arguments
x 
a numeric matrix with at least 5 rows and at least 2 columns (if

y 
a numeric vector or matrix which will be concatenated to 
type 
specifies the type of correlations to compute. Spearman correlations are the Pearson linear correlations computed on the ranks of nonmissing elements, using midranks for ties. 
... 
argument for method compatiblity. 
Details
Uses midranks in case of ties, as described by Hollander and Wolfe.
Pvalues are approximated by using the t
or F
distributions.
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 Pvalues.
Pairs with fewer than 2 nonmissing values have the r values set to NA.
The diagonals of n
are the number of nonNAs for the single variable
corresponding to that row and column.
Author(s)
Frank Harrell
Department of Biostatistics
Vanderbilt University
fh@fharrell.com
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.
See Also
hoeffd
, cor
, combine.levels
,
varclus
, dotchart3
, impute
,
chisq.test
, cut2
.
Examples
x < c(2, 1, 0, 1, 2)
y < c(4, 1, 0, 1, 4)
z < c(1, 2, 3, 4, NA)
v < c(1, 2, 3, 4, 5)
rcorr(cbind(x,y,z,v))