\HeaderA{compCorr}{Compute correlation differences and their p-values}{compCorr}
\keyword{methods}{compCorr}
\begin{Description}\relax
This function takes two correlation values (or matrices of correlation
values) and calculate the differences between these values (term by
term) and their respective p-values by a Fisher's Z transformation.
\end{Description}
\begin{Usage}
\begin{verbatim}
compCorr(n1, r1, n2, r2)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{n1}] numerical or matrix of sample sizes for group 1.
\item[\code{r1}] numerical or matrix of correlation values for group 1.
\item[\code{n2}] numerical or matrix of sample sizes for group 2.
\item[\code{r2}] numerical or matrix of correlation values for group 2.
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
This function use Fisher's Z transformation from scripts adapted from
the Internet: \\
\url{http://ftp.sas.com/techsup/download/stat/compcorr.html} \\
\url{http://www.fon.hum.uva.nl/Service/Statistics/Two_Correlations.html}
\end{Details}
\begin{Value}
The result of this function is a list with two numerical items.
\begin{ldescription}
\item[\code{diff}] matrix (or a single number) of differences between
correlation values from two groups
\item[\code{pval}] matrix (or a single number) of p-values of differences
between the correlation values
\end{ldescription}
\end{Value}
\begin{Author}\relax
Gustavo H. Esteves <\email{gesteves@vision.ime.usp.br}>
\end{Author}
\begin{Examples}
\begin{ExampleCode}
compCorr(12, 0.9, 16, 0.73)
\end{ExampleCode}
\end{Examples}

