Keng: Knock Errors Off Nice Guesses

Miscellaneous functions and data used in psychological research and teaching. Keng currently has a built-in dataset depress, and could (1) scale a vector; (2) compute the cut-off values of Pearson's r with known sample size; (3) test the significance and compute the post-hoc power for Pearson's r with known sample size; (4) conduct prior power analysis and plan the sample size for Pearson's r; (5) compare lm()'s fitted outputs using R-squared, f_squared, post-hoc power, and PRE (Proportional Reduction in Error, also called partial R-squared or partial Eta-squared); (6) calculate PRE from partial correlation, Cohen's f, or f_squared; (7) conduct prior power analysis and plan the sample size for one or a set of predictors in regression analysis; (8) conduct post-hoc power analysis for one or a set of predictors in regression analysis with known sample size.

Version:	2024.12.15
Depends:	R (≥ 2.10)
Imports:	stats
Suggests:	knitr, rmarkdown, car, effectsize, testthat (≥ 3.0.0)
Published:	2024-12-15
DOI:	10.32614/CRAN.package.Keng
Author:	Qingyao Zhang [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
Language:	en-US
Materials:	README NEWS
CRAN checks:	Keng results

Documentation:

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

Downloads:

Package source:	Keng_2024.12.15.tar.gz
Windows binaries:	r-devel: Keng_2024.12.15.zip, r-release: Keng_2024.12.15.zip, r-oldrel: Keng_2024.12.15.zip
macOS binaries:	r-release (arm64): Keng_2024.12.15.tgz, r-oldrel (arm64): Keng_2024.12.15.tgz, r-release (x86_64): Keng_2024.12.15.tgz, r-oldrel (x86_64): Keng_2024.12.15.tgz
Old sources:	Keng archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=Keng to link to this page.