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Computations of Fisher's z-tests concerning different kinds of correlation differences. Additionally, approaches to estimating statistical power via Monte Carlo simulations are implemented. Important to note, the Pearson correlation coefficient is sensitive to linear association, but also to a host of statistical issues such as univariate and bivariate outliers, range restrictions, and heteroscedasticity (e.g., Duncan & Layard, 1973 <doi:10.1093/BIOMET/60.3.551>; Wilcox, 2013 <doi:10.1016/C2010-0-67044-1>). Thus, every power analysis requires that specific statistical prerequisites are fulfilled and can be invalid if the prerequisites do not hold.
Version: | 0.8.3 |
Depends: | R (≥ 4.3.0), MASS |
Published: | 2024-05-03 |
DOI: | 10.32614/CRAN.package.diffcor |
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_0.8.3.tar.gz |
Windows binaries: | r-devel: diffcor_0.8.3.zip, r-release: diffcor_0.8.3.zip, r-oldrel: diffcor_0.8.3.zip |
macOS binaries: | r-release (arm64): diffcor_0.8.3.tgz, r-oldrel (arm64): diffcor_0.8.3.tgz, r-release (x86_64): diffcor_0.8.3.tgz, r-oldrel (x86_64): diffcor_0.8.3.tgz |
Old sources: | diffcor archive |
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These binaries (installable software) and packages are in development.
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