\name{pwr.r.test}
\alias{pwr.r.test}

\title{Power calculations for correlation test}
\description{
 Compute power of test or determine parameters to obtain target
     power (same as power.anova.test).}

\usage{
pwr.r.test(n = NULL, r = NULL, sig.level = 0.05, power = NULL,
    alternative = c("two.sided", "less","greater"))}
%- maybe also 'usage' for other objects documented here.
\arguments{
  \item{n}{Number of observations}
  \item{r}{Linear correlation coefficient}
 \item{sig.level}{Significance level (Type I error probability)}
  \item{power}{Power of test (1 minus Type II error probability)}
  \item{alternative}{a character string specifying the alternative hypothesis,
          must be one of "two.sided" (default), "greater" or
          "less"}}
\details{
These calculations use the Z' transformation of correlation coefficient :
	Z'=arctanh(r)+r/(2*(n-1)) and a bias correction is applied. Note that
	contrary to Cohen (1988) p.546, where zp' = arctanh(rp) + rp/(2*(n-1))
	and zc' = arctanh(rc) + rc/(2*(n-1)), we only use here
	zp' = arctanh(rp) + rp/(2*(n-1)) and zc' = arctanh(rc).

 Exactly one of the parameters 'r','n','power' and
     'sig.level' must be passed as NULL, and that parameter is
     determined from the others. Notice that the last one has non-NULL
     default so NULL must be explicitly passed if you want to compute
     it.

}
\value{
   Object of class '"power.htest"', a list of the arguments
     (including the computed one) augmented with 'method' and 'note'
     elements.
}
\references{Cohen, J. (1988). Statistical power analysis for the
	behavioral sciences (2nd ed.). Hillsdale,NJ: Lawrence Erlbaum.}
\author{Stephane Champely <champely@univ-lyon1.fr> but this is a mere copy of
	Peter Dalgaard work (power.t.test). The modified bias correction is
	contributed by Jeffrey Gill.}
\note{
'uniroot' is used to solve power equation for unknowns, so you may
     see errors from it, notably about inability to bracket the root
     when invalid arguments are given.
}
\examples{

## Exercise 3.1 p. 96 from Cohen (1988)
pwr.r.test(r=0.3,n=50,sig.level=0.05,alternative="two.sided")
pwr.r.test(r=0.3,n=50,sig.level=0.05,alternative="greater")

## Exercise 3.4 p. 208
pwr.r.test(r=0.3,power=0.80,sig.level=0.05,alternative="two.sided")
pwr.r.test(r=0.5,power=0.80,sig.level=0.05,alternative="two.sided")
pwr.r.test(r=0.1,power=0.80,sig.level=0.05,alternative="two.sided")
}
\keyword{htest}
