\name{rcorr} \alias{rcorr} \alias{print.rcorr} \title{Matrix of Correlations and P-values} \description{ \code{rcorr} Computes a matrix of Pearson's \code{r} or Spearman's \code{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 \code{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")) \method{print}{rcorr}(x, \dots) } \arguments{ \item{x}{ a numeric matrix with at least 5 rows and at least 2 columns (if \code{y} is absent). For \code{print}, \code{x} is an object produced by \code{rcorr}. } \item{y}{ a numeric vector or matrix which will be concatenated to \code{x}. If \code{y} is omitted for \code{rcorr}, \code{x} must be a matrix. } \item{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. } \item{\dots}{argument for method compatiblity.} } \value{ \code{rcorr} returns a list with elements \code{r}, the matrix of correlations, \code{n} the matrix of number of observations used in analyzing each pair of variables, and \code{P}, the asymptotic P-values. Pairs with fewer than 2 non-missing values have the r values set to NA. The diagonals of \code{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 \code{t} or \code{F} distributions. } \author{ Frank Harrell \cr Department of Biostatistics \cr Vanderbilt University \cr \email{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. } \seealso{ \code{\link{hoeffd}}, \code{\link{cor}}, \code{\link{combine.levels}}, \code{\link{varclus}}, \code{\link{dotchart3}}, \code{\link{impute}}, \code{\link{chisq.test}}, \code{\link{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)) } \keyword{nonparametric} \keyword{htest} \keyword{category}