Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/test.diff.cor.R
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 Z-score 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 Z-scores for the hypothesis. |
|
A numeric matrix of the P-values. |
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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