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Keng: Knock Errors Off Nice Guesses

Miscellaneous functions and data used in Qingyao's psychological research and teaching. Keng currently has a built-in dataset depress, and could (1) scale a vector, (2) test the significance and compute the cut-off values of Pearson's r without raw data, (3) compare lm()'s fitted outputs using R-squared and PRE (Proportional Reduction in Error, also called partial R-squared or partial Eta-squared).

Version: 2024.11.17
Depends: R (≥ 2.10)
Imports: stats
Suggests: knitr, rmarkdown, car, effectsize, testthat (≥ 3.0.0)
Published: 2024-11-17
DOI: 10.32614/CRAN.package.Keng
Author: Qingyao Zhang ORCID iD [aut, cre]
Maintainer: Qingyao Zhang <qingyaozhang at outlook.com>
BugReports: https://github.com/qyaozh/Keng/issues
License: CC BY 4.0
URL: https://github.com/qyaozh/Keng
NeedsCompilation: no
Materials: README NEWS
CRAN checks: Keng results

Documentation:

Reference manual: Keng.pdf
Vignettes: PRE (source, R code)
PartialRegression (source, R code)

Downloads:

Package source: Keng_2024.11.17.tar.gz
Windows binaries: r-devel: Keng_2024.11.17.zip, r-release: Keng_2024.11.17.zip, r-oldrel: Keng_2024.11.17.zip
macOS binaries: r-release (arm64): Keng_2024.11.17.tgz, r-oldrel (arm64): Keng_2024.11.17.tgz, r-release (x86_64): Keng_2024.11.17.tgz, r-oldrel (x86_64): Keng_2024.11.17.tgz
Old sources: Keng archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.