Matrix of Correlations and P-values
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.
rcorr(x, y, type=c("pearson","spearman"))
## S3 method for class 'rcorr'
print(x, ...)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 non-missing elements, using midranks for ties. |
... |
argument for method compatiblity. |
Uses midranks in case of ties, as described by Hollander and Wolfe.
P-values are approximated by using the t or F distributions.
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.
Frank Harrell
Department of Biostatistics
Vanderbilt University
fh@fharrell.com
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.
hoeffd, cor, combine.levels,
varclus, dotchart3, impute,
chisq.test, cut2.
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))
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.