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MultiLevelOptimalBayes

0.0.4.0

Regularized Bayesian Estimator for Two-Level Latent Variable Models

0packages depend
2.2Kdownloads / year
79.1%test coverage
13/13checks pass

Overview

About
Maintained by Valerii DashukFirst published 2025-05-275 releasesCRAN page ↗

Implements a regularized Bayesian estimator that optimizes the estimation of between-group coefficients for multilevel latent variable models by minimizing mean squared error (MSE) and balancing variance and bias. The package provides more reliable estimates in scenarios with limited data, offering a robust solution for accurate parameter estimation in two-level latent variable models. It is designed for researchers in psychology, education, and related fields who face challenges in estimating between-group effects under small sample sizes and low intraclass correlation coefficients. The package includes comprehensive S3 methods for result objects: print(), summary(), coef(), se(), vcov(), confint(), as.data.frame(), dim(), length(), names(), and update() for enhanced usability and integration with standard R workflows. Dashuk et al. (2025a) doi:10.1017/psy.2025.10045 derived the optimal regularized Bayesian estimator; Dashuk et al. (2025b) doi:10.1007/s41237-025-00264-7 extended it to the multivariate case; and Luedtke et al. (2008) doi:10.1037/a0012869 formalized the two-level latent variable framework.

Install

Health

CRAN checks
13OK
Slowest check: 14.5 min · r-devel-windows-x86_64
Code health
Yes
Tests · ratio 0.03
79.1%
Coverage · measured lines
100%
Documentation · exports
1
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 371 wordsVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
50%
References docs
6%

Downloads

2.2K
CRAN downloads in the past year
Rank #23,182 · ~6/day · ~187/mo
Daily download trend is not available in this view yet.
11630 days
44990 days
2.2K1 year
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Also on121 r2u23 autocran

Dependencies

Declared dependencies
4 external dependencies (excludes base and recommended)
Depends (1)
R >= 4.1.0
Imports (1)
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (4)
Maintainer (1)
Author, Maintainer
Authors (4)
Author, Maintainer
Package Timeline

5 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.0.4.0Latest
    2025-09-23 · current release · diff ↗
  • 0.0.3.0
    2025-09-11 · diff ↗
  • 0.0.2.0
    2025-07-12 · diff ↗
  • 0.0.1.6
    2025-05-29 · diff ↗
  • 0.0.1.5
    2025-05-27
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-05-27
Total releases
5 / 1 yrs
License
GPL-3 OSI
Minimum R
≥ 4.1.0
Download size
47 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("MultiLevelOptimalBayes")
Dashuk, V., Hecht, M., Timilsina, B., & Zitzmann, S. (2025). MultiLevelOptimalBayes: Regularized Bayesian Estimator for Two-Level Latent Variable Models (Version 0.0.4.0) [Computer software]. https://doi.org/10.32614/CRAN.package.MultiLevelOptimalBayes

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for MultiLevelOptimalBayes version 0.0.4.0 [Data set]. HJJB, LLC. Data release v2026-08-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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