Package: MultiLevelOptimalBayes
Type: Package
Title: Regularized Bayesian Estimator for Two-Level Latent Variable
        Models
Version: 0.0.2.0
Authors@R: c(person("Valerii", "Dashuk", role = c("aut", "cre"), email = "vadashuk@gmail.com"),
	person("Binayak", "Timilsina", role = "aut", email = "binayak.timilsina001@gmail.com"),
	person("Martin", "Hecht", role = "aut", email = "martin.hecht@hsu-hh.de"),
	person("Steffen", "Zitzmann", role = "aut", email = "steffen.zitzmann@medicalschool-hamburg.de")
	)
Author: Valerii Dashuk [aut, cre],
  Binayak Timilsina [aut],
  Martin Hecht [aut],
  Steffen Zitzmann [aut]
Maintainer: Valerii Dashuk <vadashuk@gmail.com>
Description: 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. Dashuk et al. (2024) <doi:10.13140/RG.2.2.18148.39048>
 derived the optimal regularized Bayesian estimator;
 Dashuk et al. (2024) <doi:10.13140/RG.2.2.34350.01604> extended it to 
 the multivariate case; and Luedtke et al. (2008) <doi:10.1037/a0012869>
 formalized the two-level latent variable framework.
Imports: pracma
License: GPL-3
Depends: R (>= 4.1.0)
Encoding: UTF-8
RoxygenNote: 7.3.2
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-07-11 21:33:27 UTC; valerii.dashuk
Repository: CRAN
Date/Publication: 2025-07-11 22:20:07 UTC
Built: R 4.3.3; ; 2025-07-14 21:56:28 UTC; unix
