betaNB

betaNB: Generates nonparametric bootstrap confidence intervals for standardized regression coefficients and other effect sizes for models fitted by lm().

https://github.com/jeksterslab/betanb

Science Score: 57.0%

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Keywords

confidence-intervals nonparametric-bootstrap r r-package regression-effect-sizes standardized-regression-coefficients

Last synced: 7 months ago · JSON representation ·

Repository

betaNB: Generates nonparametric bootstrap confidence intervals for standardized regression coefficients and other effect sizes for models fitted by lm().

Basic Info

Host: GitHub
Owner: jeksterslab
License: other
Language: TeX
Default Branch: main
Homepage: https://jeksterslab.github.io/betaNB/
Size: 19.7 MB

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Topics

confidence-intervals nonparametric-bootstrap r r-package regression-effect-sizes standardized-regression-coefficients

Created almost 3 years ago · Last pushed 8 months ago

Metadata Files

Readme Changelog License Citation

betaNB

Ivan Jacob Agaloos Pesigan 2025-07-22

$Compile LaTeX$

Description

Generates nonparametric bootstrap confidence intervals (Efron & Tibshirani, 1993: https://doi.org/10.1201/9780429246593) for standardized regression coefficients (beta) and other effect sizes, including multiple correlation, semipartial correlations, improvement in R-squared, squared partial correlations, and differences in standardized regression coefficients, for models fitted by lm().

Installation

You can install the CRAN release of betaNB with:

r install.packages("betaNB")

You can install the development version of betaNB from GitHub with:

r if (!require("remotes")) install.packages("remotes") remotes::install_github("jeksterslab/betaNB")

Example

In this example, a multiple regression model is fitted using program quality ratings (QUALITY) as the regressand/outcome variable and number of published articles attributed to the program faculty members (NARTIC), percent of faculty members holding research grants (PCTGRT), and percentage of program graduates who received support (PCTSUPP) as regressor/predictor variables using a data set from 1982 ratings of 46 doctoral programs in psychology in the USA (National Research Council, 1982). Confidence intervals for the standardized regression coefficients are generated using the BetaNB() function from the betaNB package.

r library(betaNB)

r df <- betaNB::nas1982

Regression

Fit the regression model using the lm() function.

r object <- lm(QUALITY ~ NARTIC + PCTGRT + PCTSUPP, data = df)

Nonparametric Bootstrap

r nb <- NB(object)

Standardized Regression Slopes

``` r BetaNB(nb, alpha = 0.05)

> Call:

> BetaNB(object = nb, alpha = 0.05)

>

> Standardized regression slopes

> type = "pc"

> est se R 2.5% 97.5%

> NARTIC 0.4951 0.0714 5000 0.3521 0.6361

> PCTGRT 0.3915 0.0760 5000 0.2377 0.5382

> PCTSUPP 0.2632 0.0796 5000 0.1076 0.4157

```

Other Effect Sizes

The betaNB package also has functions to generate nonparametric bootstrap confidence intervals for other effect sizes such as RSqNB() for multiple correlation coefficients (R-squared and adjusted R-squared), DeltaRSqNB() for improvement in R-squared, SCorNB() for semipartial correlation coefficients, PCorNB() for squared partial correlation coefficients, and DiffBetaNB() for differences of standardized regression coefficients.

Multiple Correlation Coefficients (R-squared and adjusted R-squared)

References

Efron, B., & Tibshirani, R. J. (1993). *An introduction to the bootstrap*. Chapman & Hall.

National Research Council. (1982). *An assessment of research-doctorate programs in the United States: Social and behavioral sciences*. National Academies Press.

Pesigan, I. J. A. (2022). *Confidence intervals for standardized coefficients: Applied to regression coefficients in primary studies and indirect effects in meta-analytic structural equation modeling* \[PhD thesis\]. University of Macau.

Owner

Name: Ivan Jacob Agaloos Pesigan
Login: jeksterslab
Kind: user
Company: University of Macau

Repositories: 25
Profile: https://github.com/jeksterslab

Citation (CITATION.cff)

# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "betaNB" in publications use:'
type: software
license: MIT
title: 'betaNB: Bootstrap for Regression Effect Sizes'
version: 1.0.6
identifiers:
- type: doi
  value: 10.32614/CRAN.package.betaNB
abstract: 'Generates nonparametric bootstrap confidence intervals (Efron and Tibshirani,
  1993: <https://doi.org/10.1201/9780429246593>) for standardized regression coefficients
  (beta) and other effect sizes, including multiple correlation, semipartial correlations,
  improvement in R-squared, squared partial correlations, and differences in standardized
  regression coefficients, for models fitted by lm().'
authors:
- family-names: Pesigan
  given-names: Ivan Jacob Agaloos
  email: r.jeksterslab@gmail.com
  orcid: https://orcid.org/0000-0003-4818-8420
preferred-citation:
  type: thesis
  title: 'Confidence intervals for standardized coefficients: Applied to regression
    coefficients in primary studies and indirect effects in meta-analytic structural
    equation modeling'
  authors:
  - family-names: Pesigan
    given-names: Ivan Jacob Agaloos
    email: r.jeksterslab@gmail.com
    orcid: https://orcid.org/0000-0003-4818-8420
  year: '2022'
  institution:
    name: University of Macau
  thesis-type: PhD Thesis
repository: https://CRAN.R-project.org/package=betaNB
repository-code: https://github.com/jeksterslab/betaNB
url: https://jeksterslab.github.io/betaNB/
contact:
- family-names: Pesigan
  given-names: Ivan Jacob Agaloos
  email: r.jeksterslab@gmail.com
  orcid: https://orcid.org/0000-0003-4818-8420
keywords:
- confidence-intervals
- nonparametric-bootstrap
- r
- r-package
- regression-effect-sizes
- standardized-regression-coefficients
references:
- type: manual
  title: 'betaNB: Bootstrap for Regression Effect Sizes'
  authors:
  - family-names: Pesigan
    given-names: Ivan Jacob Agaloos
    email: r.jeksterslab@gmail.com
    orcid: https://orcid.org/0000-0003-4818-8420
  year: '2023'

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cran.r-project.org: betaNB

Bootstrap for Regression Effect Sizes

Homepage: https://github.com/jeksterslab/betaNB
Documentation: http://cran.r-project.org/web/packages/betaNB/betaNB.pdf
License: MIT + file LICENSE
Latest release: 1.0.5
published about 1 year ago

Versions: 5
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 255 Last month
Docker Downloads: 2,145

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Forks count: 28.8%

Dependent packages count: 29.7%

Stargazers count: 35.2%

Dependent repos count: 35.3%

Average: 43.7%

Downloads: 89.7%

Maintainers (1)

r.jeksterslab@gmail.com

Last synced: 7 months ago

betaNB

Science Score: 57.0%

Keywords

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

betaNB

Description

Installation

Example

Regression

Nonparametric Bootstrap

Standardized Regression Slopes

> Call:

> BetaNB(object = nb, alpha = 0.05)

>

> Standardized regression slopes

> type = "pc"

> est se R 2.5% 97.5%

> NARTIC 0.4951 0.0714 5000 0.3521 0.6361

> PCTGRT 0.3915 0.0760 5000 0.2377 0.5382

> PCTSUPP 0.2632 0.0796 5000 0.1076 0.4157

Other Effect Sizes

Multiple Correlation Coefficients (R-squared and adjusted R-squared)

> Call:

> RSqNB(object = nb, alpha = 0.05)

>

> R-squared and adjusted R-squared

> type = "pc"

> est se R 2.5% 97.5%

> rsq 0.8045 0.0533 5000 0.692 0.8975

> adj 0.7906 0.0571 5000 0.670 0.8902

Improvement in R-squared

> Call:

> DeltaRSqNB(object = nb, alpha = 0.05)

>

> Improvement in R-squared

> type = "pc"

> est se R 2.5% 97.5%

> NARTIC 0.1859 0.0581 5000 0.0811 0.3069

> PCTGRT 0.1177 0.0487 5000 0.0368 0.2286

> PCTSUPP 0.0569 0.0343 5000 0.0091 0.1405

Semipartial Correlation Coefficients

> Call:

> SCorNB(object = nb, alpha = 0.05)

>

> Semipartial correlations

> type = "pc"

> est se R 2.5% 97.5%

> NARTIC 0.4312 0.0686 5000 0.2847 0.5540

> PCTGRT 0.3430 0.0721 5000 0.1917 0.4782

> PCTSUPP 0.2385 0.0715 5000 0.0953 0.3749

Squared Partial Correlation Coefficients

> Call:

> PCorNB(object = nb, alpha = 0.05)

>

> Squared partial correlations

> type = "pc"

> est se R 2.5% 97.5%

> NARTIC 0.4874 0.0969 5000 0.2873 0.6624

> PCTGRT 0.3757 0.1079 5000 0.1632 0.5861

> PCTSUPP 0.2254 0.1156 5000 0.0429 0.4832

Differences of Standardized Regression Coefficients

> Call:

> DiffBetaNB(object = nb, alpha = 0.05)

>

> Differences of standardized regression slopes

> type = "pc"

> est se R 2.5% 97.5%

> NARTIC-PCTGRT 0.1037 0.1302 5000 -0.1472 0.3651

> NARTIC-PCTSUPP 0.2319 0.1235 5000 -0.0055 0.4766

> PCTGRT-PCTSUPP 0.1282 0.1274 5000 -0.1152 0.3831

Documentation

References

Owner

Citation (CITATION.cff)

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