diffcor: Fisher's z-Tests Concerning Difference of Correlations

Computations of Fisher's z-tests concerning differences between correlations. diffcor.one() can be used to test whether an expected value differs from an observed value, for example, in construct validation. diffcor.two() can be used to test if the correlation between two constructs differed between two studies. diffcor.dep() can be applied to check if the correlation between two constructs (r12) is significantly different from the correlation of the first construct with a third one (r13), given the intercorrelation of the compared constructs (r23). All outputs provide the compared correlations, test statistic in z-units, and p-values. For diffcor.one() and diffcor.two(), the output further provides confidence intervals of the empirical correlations and the effect size Cohens q. According to Cohen (1988), q = |.10|, |.30| and |.50| are considered small, moderate, and large differences, respectively.

Version: 0.7.1
Published: 2022-05-05
Author: Christian Blötner
Maintainer: Christian Blötner <c.bloetner at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: diffcor results


Reference manual: diffcor.pdf


Package source: diffcor_0.7.1.tar.gz
Windows binaries: r-devel: diffcor_0.7.1.zip, r-release: diffcor_0.7.1.zip, r-oldrel: diffcor_0.7.1.zip
macOS binaries: r-release (arm64): diffcor_0.7.1.tgz, r-oldrel (arm64): diffcor_0.7.1.tgz, r-release (x86_64): diffcor_0.7.1.tgz, r-oldrel (x86_64): diffcor_0.7.1.tgz
Old sources: diffcor archive


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