Description Usage Arguments Details Value Author(s) References See Also Examples
This functions tests the hypothesis of no difference in correlations. It uses
the Fisher Z transform (atanh
) to test the null hypothesis
of no difference in correlations. See details.
1 2 3 4 
X1 
A 
X2 
A 
cor1 
A 
cor2 
A 
n1 

n2 

alternative 
The alternative hypothesis. 
conf.level 
The confidence level used in the computed confidence intervals. 
null 
A matrix of number giving the difference in correlation under the null hypothesis. 
The function uses the Fisher Z transform (atanh
) of
correlations to test that the hypotheses of no difference in correlation.
The computed Zscore is
(Z_1  Z_2)/ sqrt(1/(n_1  3) + 1/(n_2  3))
where Z_1 and Z_2 are the Fisher transformed correlations. It performs the test for all correlations in the correlation matrix.
A list of matrices or vector containing:

The lower confidence interval limit. 

The upper confidence interval limit. 

A numeric matrix of Zscores for the hypothesis. 

A numeric matrix of the Pvalues. 
with an attribute giving the alternative hypothesis.
Anders Ellern Bilgrau <anders.ellern.bilgrau (at) gmail.com>
http://core.ecu.edu/psyc/wuenschk/docs30/CompareCorrCoeff.pdf
Similar usage to cor.test
(but NOT the same thing).
This is a vectorised version of test.diff.cor.single
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14  n1 < 8
n2 < 10
X1 < createData(n = n1, m = 5)
X2 < createData(n = n2, m = 5)
print(cor1 < cor(X1))
print(cor2 < cor(X2))
test.diff.cor(X1, X2)
# Directly supplied correlation matrices
test.diff.cor(cor1 = cor1, cor2 = cor2, n1 = n1, n2 = n2)
test.diff.cor(X1, X2, alternative = "less")

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