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.

Package details

AuthorQingyao Zhang [aut, cre] (<https://orcid.org/0000-0002-6891-5982>)
MaintainerQingyao Zhang <qingyaozhang@outlook.com>
LicenseCC BY 4.0
Version2024.12.15
URL https://github.com/qyaozh/Keng
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("Keng")

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Keng documentation built on April 4, 2025, 1:37 a.m.