Package: stdmod 0.2.13

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 (2022) <doi:10.1037/hea0001188>. Also includes simple-to-use functions for computing conditional effects (unstandardized or standardized) and plotting moderation effects.

Authors:Shu Fai Cheung [aut, cre], David Weng Ngai Vong [ctb]

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manual.pdf |manual.html✨
card.svg |card.png
stdmod/json (API)
NEWS

# Install 'stdmod' in R:
install.packages('stdmod', repos = c('https://sfcheung.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sfcheung/stdmod/issues

Pkgdown/docs site:https://sfcheung.github.io

Datasets:

On CRAN:

Conda:

bootstrappingconfidence-intervaleffect-sizesmoderationregressionstandardizationstandardized-moderation

5.63 score 1 stars 47 scripts 384 downloads 8 exports 36 dependencies

Last updated from:7956549ea9. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK183
source / vignettesOK175
linux-release-x86_64OK182
macos-release-arm64OK92
macos-oldrel-arm64OK146
windows-develOK108
windows-releaseOK112
windows-oldrelOK104
wasm-releaseOK116

Exports:cond_effectcond_effect_bootplotmodstd_selectedstd_selected_bootstdmodstdmod_bootstdmod_lavaan

Dependencies:bootclicpp11farverggplot2glueGPArotationgtableigraphisobandlabelinglatticelavaanlifecyclelmhelprsmagrittrmanymomeMASSMatrixmnormtnlmenumDerivpbapplypbivnormpkgconfigpsychquadprogR6RColorBrewerrlangS7scalessemToolsvctrsviridisLitewithr

A Quick Start Guide on Using std_selected()

Shu Fai Cheung

Rendered fromstdmod.Rmdusingknitr::rmarkdownon Jun 02 2026.

Last update: 2026-01-04
Started: 2022-04-13

Conditional Effects by cond_effect()

Shu Fai Cheung

Rendered fromcond_effect.Rmdusingknitr::rmarkdownon Jun 02 2026.

Last update: 2023-09-09
Started: 2022-05-05

Mean Center and Standardize Selected Variable by std_selected()

Shu Fai Cheung and David Weng Ngai Vong

Rendered fromstd_selected.Rmdusingknitr::rmarkdownon Jun 02 2026.

Last update: 2026-01-04
Started: 2022-05-05

Moderation Effects Plots by plotmod()

Shu Fai Cheung

Rendered fromplotmod.Rmdusingknitr::rmarkdownon Jun 02 2026.

Last update: 2023-03-26
Started: 2022-05-05

Standardized Moderation Effect by std_selected()

Shu Fai Cheung and David Weng Ngai Vong

Rendered frommoderation.Rmdusingknitr::rmarkdownon Jun 02 2026.

Last update: 2026-01-04
Started: 2022-05-05

Standardized Moderation Effect in a Path Model by stdmod_lavaan()

Shu Fai Cheung and David Weng Ngai Vong

Rendered fromstdmod_lavaan.Rmdusingknitr::rmarkdownon Jun 02 2026.

Last update: 2026-01-04
Started: 2022-05-05

Readme and manuals

Help Manual

Help pageTopics
The 'add1' Method for a 'std_selected' Class Objectadd1.std_selected
Conditional Effect in a 'cond_effect'-Class Objectcoef.cond_effect
Standardized Moderation Effect in a 'stdmod_lavaan' Class Objectcoef.stdmod_lavaan
Conditional Effectscond_effect cond_effect_boot
Confidence Intervals for a 'cond_effect' Class Objectconfint.cond_effect
Confidence Intervals for a 'std_selected' Class Objectconfint.std_selected
Confidence Intervals for a 'stdmod_lavaan' Class Objectconfint.stdmod_lavaan
Moderation Effect Plotplotmod
Print a 'cond_effect' Class Objectprint.cond_effect
Print Basic Information of a 'std_selected' Class Objectprint.std_selected
Print a 'stdmod_lavaan' Class Objectprint.stdmod_lavaan
Print the Summary of a 'std_selected' Class Objectprint.summary.std_selected
Sample Dataset: Predicting Sleep Durationsleep_emo_con
Standardize Variables in a Regression Modelstd_selected std_selected_boot
Standardized Moderation Effect Given an 'lm' Outputstdmod stdmod_boot
Standardized Moderation Effect and Its Bootstrap CI in 'lavaan'stdmod_lavaan
Summary Method for a 'std_selected' Class Objectsummary.std_selected
Sample Dataset: A Path Model With A Moderatortest_mod1
Sample Dataset: A Path Model With A Moderatortest_mod2
Sample Dataset: A Path Model With A Moderatortest_mod3_miss
Sample Dataset: One IV, One Moderator, Two Covariatestest_x_1_w_1_v_1_cat1_n_500
Sample Dataset: One IV, One Moderator, Two Covariatestest_x_1_w_1_v_1_cat1_xw_cov_n_500
Sample Dataset: One IV, One 3-Category Moderator, Two Covariatestest_x_1_w_1_v_1_cat1_xw_cov_wcat3_n_500
Sample Dataset: One IV, One Moderator, Two Covariatestest_x_1_w_1_v_2_n_500
The 'update' Method for a 'std_selected' Class Objectupdate.std_selected
The 'vcov' Method for a 'std_selected' Class Objectvcov.std_selected