\name{fisherz} \alias{fisherz} \alias{fisherz2r} \alias{r.con}\alias{r2c} \alias{r2t} \alias{t2r} \alias{g2r} \alias{chi2r} \alias{r2chi} \alias{cor2cov} \title{Transformations of r, d, and t including Fisher r to z and z to r and confidence intervals} \description{Convert a correlation to a z or t, or d, or chi or covariance matrix or z to r using the Fisher transformation or find the confidence intervals for a specified correlation. r2d converts a correlation to an effect size (Cohen's d) and d2r converts a d into an r. g2r converts Hedge's g to a correlation. t2r converts a t test to r, r2t converts a correlation to a t-test value. chi2r converts a chi square to r, r2chi converts it back. r2c and cor2cov convert a correlation matrix to a covariance matrix. d2t and t2d convert cohen's d into a t and a t into a cohen d. See \code{\link{cohen.d}} for other conversions. } \usage{ fisherz(rho) fisherz2r(z) r.con(rho,n,p=.95,twotailed=TRUE) r2t(rho,n) t2r(t,df) g2r(g,df,n) chi2r(chi2,n) r2chi(rho,n) r2c(rho,sigma) cor2cov(rho,sigma) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{rho}{ a Pearson r } \item{z}{A Fisher z} \item{n}{Sample size for confidence intervals} \item{df}{degrees of freedom for t, or g} \item{p}{Confidence interval} \item{twotailed}{Treat p as twotailed p} \item{g}{An effect size (Hedge's g)} \item{t}{A student's t value} \item{chi2}{A chi square} \item{sigma}{a vector of standard deviations to be used to convert a correlation matrix to a covariance matrix} } \value{ \item{z}{ value corresponding to r (fisherz)} \item{r}{r corresponding to z (fisherz2r)} \item{r.con}{lower and upper p confidence intervals (r.con)} \item{t}{t with n-2 df (r2t)} \item{r}{r corresponding to effect size d or d corresponding to r.} \item{r2c}{r2c is the reverse of the cor2con function of base R. It just converts a correlation matrix to the corresponding covariance matrix given a vector of standard deviations.} } \author{ Maintainer: William Revelle \email{revelle@northwestern.edu } } \examples{ n <- 30 r <- seq(0,.9,.1) d <- r2d(r) rc <- matrix(r.con(r,n),ncol=2) t <- r*sqrt(n-2)/sqrt(1-r^2) p <- (1-pt(t,n-2))*2 r1 <- t2r(t,(n-2)) r2 <- d2r(d) chi <- r2chi(r,n) r3 <- chi2r(chi,n) r.rc <- data.frame(r=r,z=fisherz(r),lower=rc[,1],upper=rc[,2],t=t,p=p,d=d, chi2=chi,d2r=r2,t2r=r1,chi2r=r3) round(r.rc,2) } \keyword{ multivariate }% at least one, from doc/KEYWORDS \keyword{ models }% __ONLY ONE__ keyword per line