'convert' converts from one system of units to another system of units.
This function is still under construction.

'copy.jmfuns' copies \r\jmfuns.rda (JM's R function file) to a series of locations on the hard drive.  This has the effect of keeping all versions of jmfuns.rda updated to the current version, which is located in \r.

WARNING:  copy.jmfuns copies \r\jmfuns.rda to the other locations without checking whether the source file has an earlier or later file modification date and time.  This is done because the file copy operation in R sets the date of the resulting file to the current date/time, so that, under unusual circumstances, a more recent version of \r\jmfuns.rda will have an earlier date than the corresponding file in the destination directories.  

ARGUMENTS:

Set 'feedback = TRUE' (default) for feedback regarding which copy operations were successful.  Set 'feedback = FALSE' to omit this feedback.

See html documentation for copyFileCurr.

'cor.cor.test' computes a z-test for a difference between
correlated correlation coefficients.  Let 'W', 'U', and
'V' be 3 variables of length K, all measured on the same
units.  'cor.cor.test' tests whether the correlation between
'W' and 'U' differs from the correlation between 'W' and
'V'.
'cor.cor.test' has 4 formal arguments: 'yy', 'aa', 'bb', 'N'.
These arguments can be specified in one of four ways (assume
that W, U, V and K are defined as above:
Option 1: 'yy = W', 'aa = U' & 'bb = V' and 'N' has its default value (NA).
Option 2: 'yy = cbind(W, U, V)' and 'N' has its default value (NA).
Option 3: The user has already computed 'r1 <- cor(W, U)',
'r2 <- cor(W, V)', and 'rx <- cor(U, V)'.  Then 'yy = r1', 'aa = r2'
'bb = rx', and 'N = K'.
Option 4:  Again, the user has already computed 'r1 <- cor(W, U)',
'r2 <- cor(W, V)', and 'rx <- cor(U, V)'.  Then 'yy = c(r1, r2, rx)'
and 'N = K'.
Basically, 'cor.cor.test' allows different ways to specify the input.
Options 1 - 4 all yield the same results.
The output of the function is 'z1 - z2' where 'z1' and 'z2' are
Fisher z transforms of 'r1' and 'r2'; the p-value and standard
error of 'z1 - z2'.