stdmod: Standardized Moderation Effect and Its Confidence Interval

Functions for computing a standardized moderation effect in moderated regression and forming its confidence interval by nonparametric bootstrapping as proposed in Cheung, Cheung, Lau, Hui, and Vong (2002) <doi:10.1037/hea0001188>. Also includes simple-to-use functions for computing conditional effects (unstandardized or standardized) and plotting moderation effects.

Depends: R (≥ 4.0.0)
Imports: boot, ggplot2, stats
Suggests: testthat, dplyr, knitr, rmarkdown, lavaan, visreg, lm.beta
Published: 2022-05-11
Author: Shu Fai Cheung ORCID iD [aut, cre], David Weng Ngai Vong [ctb]
Maintainer: Shu Fai Cheung <shufai.cheung at>
License: GPL-3
NeedsCompilation: no
Citation: stdmod citation info
Materials: README NEWS
CRAN checks: stdmod results


Reference manual: stdmod.pdf
Vignettes: Conditional Effects by cond_effect()
Standardized Moderation Effect by std_selected()
Moderation Effects Plots by plotmod()
Mean Center and Standardize Selected Variable by std_selected()
A Quick Start Guide on Using std_selected()
Standardized Moderation Effect in a Path Model by stdmod_lavaan()


Package source: stdmod_0.1.7.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): stdmod_0.1.7.1.tgz, r-oldrel (arm64): stdmod_0.1.7.1.tgz, r-release (x86_64): stdmod_0.1.7.1.tgz, r-oldrel (x86_64): stdmod_0.1.7.1.tgz


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