Package: betaselectr 0.2.1

betaselectr: Betas-Select in Structural Equation Models and Linear Models

It computes betas-select, coefficients after standardization in structural equation models and regression models, standardizing only selected variables. Supports models with moderation, with product terms formed after standardization. It also offers confidence intervals that account for standardization, including bootstrap confidence intervals as proposed by Cheung et al. (2022) <doi:10.1037/hea0001188>. An introduction to the package can be found in Sun et al. (2026) <doi:10.1080/00273171.2026.2672692>.

Authors:Shu Fai Cheung [aut, cre], Rong Wei Sun [aut], Florbela Chang [aut], Wendie Yang [aut], Sing-Hang Cheung [aut]

betaselectr_0.2.1.tar.gz
betaselectr_0.2.1.zip(r-4.7)betaselectr_0.2.1.zip(r-4.6)betaselectr_0.2.1.zip(r-4.5)
betaselectr_0.2.1.tgz(r-4.6-any)betaselectr_0.2.1.tgz(r-4.5-any)
betaselectr_0.2.1.tar.gz(r-4.7-any)betaselectr_0.2.1.tar.gz(r-4.6-any)
betaselectr_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
betaselectr/json (API)

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

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

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

Datasets:

On CRAN:

Conda:

bootstrappingconfidence-intervalsgeneralized-linear-modelslavaanlogistic-regressionregressionsemstandardizationstructural-equation-modeling

4.88 score 1 stars 9 scripts 430 downloads 5 exports 37 dependencies

Last updated from:a74537fbf3. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK246
source / vignettesOK228
linux-release-x86_64OK208
macos-release-arm64OK102
macos-oldrel-arm64OK126
windows-develOK122
windows-releaseOK101
windows-oldrelOK108
wasm-releaseOK134

Exports:glm_betaselectlav_betaselectlm_betaselectraw_outputstd_data

Dependencies:bootclicpp11farverggplot2glueGPArotationgtableigraphisobandlabelinglatticelavaanlavaan.printerlifecyclelmhelprsmagrittrmanymomeMASSMatrixmnormtnlmenumDerivpbapplypbivnormpkgconfigpsychquadprogR6RColorBrewerrlangS7scalessemToolsvctrsviridisLitewithr

Beta-Select Demonstration: Logistic Regression by glm()
Introduction | Data and Model | Problems With Standardization | Beta-Select by glm_betaselect() | Estimates Only | Estimates and Bootstrap Confidence Interval | Estimates and Bootstrap Confidence Intervals, With Only Selected Variables Standardized | Categorical Variables | Conclusion | References
Rendered frombetaselectr_glm.Rmdusingknitr::rmarkdown

Last update: 2026-06-10
Started: 2024-10-29

Beta-Select Demonstration: Regression by lm()
Introduction | Data and Model | Problems With Standardization | Beta-Select by lm_betaselect() | Estimates Only | Estimates and Bootstrap Confidence Interval | Estimates and Bootstrap Confidence Intervals, With Only Selected Variables Standardized | Categorical Variables | Conclusion | References
Rendered frombetaselectr_lm.Rmdusingknitr::rmarkdown

Last update: 2026-06-10
Started: 2024-10-29

Beta-Select Demonstration: SEM by 'lavaan'
Introduction | Data and Model | Problems With Standardization | Beta-Select lav_betaselect() | Estimates Only | Estimates and Bootstrap Confidence Interval | Estimates and Bootstrap Confidence Intervals, With Only Selected Variables Standardized | Categorical Variables | Conclusion | References
Rendered frombetaselectr_lav.Rmdusingknitr::rmarkdown

Last update: 2026-06-10
Started: 2024-10-06

Readme and manuals

Help Manual

Help pageTopics
ANOVA Tables For 'lm_betaselect' and 'glm_betaselect' Objectsanova.glm_betaselect anova.lm_betaselect
Coefficients of a 'lav_betaselect'-Class Objectcoef.lav_betaselect
Coefficients of Beta-Select in Linear Modelscoef.glm_betaselect coef.lm_betaselect
Confidence Intervals for a 'lav_betaselect'-Class Objectconfint.lav_betaselect
Confidence Interval for 'lm_betaselect' or 'glm_betaselect' Objectsconfint.glm_betaselect confint.lm_betaselect
Test Dataset with Moderator and Mediatordata_test_medmod
Test Dataset with Moderator and Categorical Variablesdata_test_mod_cat
Test Dataset with a Binary Outcome Variabledata_test_mod_cat_binary
Test Dataset with Moderator and Categorical Variables (Version 2)data_test_mod_cat2
Call in an 'lm_betaselect' or 'glm_betaselect' ObjectgetCall.glm_betaselect getCall.lm_betaselect
Betas-Select in a 'lavaan'-Modellav_betaselect
Betas-Select in a Regression Modelglm_betaselect lm_betaselect print.glm_betaselect print.lm_betaselect raw_output
Predict Method for a 'glm_betaselect' Objectpredict.glm_betaselect
Predict Method for an 'lm_betaselect' Objectpredict.lm_betaselect
Print a 'lav_betaselect' Objectprint.lav_betaselect
Standardize Selected Variablesstd_data
Summary of an 'glm_betaselect'-Class Objectprint.summary.glm_betaselect summary.glm_betaselect
Summary of an 'lm_betaselect'-Class Objectprint.summary.lm_betaselect summary.lm_betaselect
The 'vcov' Method for 'lm_betaselect' and 'glm_betaselect' Objectsvcov.glm_betaselect vcov.lm_betaselect