# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "MIRES" in publications use:' type: software license: MIT title: 'MIRES: Measurement Invariance Assessment Using Random Effects Models and Shrinkage' version: 0.1.1 doi: 10.32614/CRAN.package.MIRES abstract: Estimates random effect latent measurement models, wherein the loadings, residual variances, intercepts, latent means, and latent variances all vary across groups. The random effect variances of the measurement parameters are then modeled using a hierarchical inclusion model, wherein the inclusion of the variances (i.e., whether it is effectively zero or non-zero) is informed by similar parameters (of the same type, or of the same item). This additional hierarchical structure allows the evidence in favor of partial invariance to accumulate more quickly, and yields more certain decisions about measurement invariance. Martin, Williams, and Rast (2020) . authors: - family-names: Martin given-names: Stephen email: stephenSRMMartin@gmail.com orcid: https://orcid.org/0000-0001-8085-2390 - family-names: Rast given-names: Philippe email: rast.ph@gmail.com orcid: https://orcid.org/0000-0003-3630-6629 repository: https://cran.r-universe.dev repository-code: https://github.com/stephenSRMMartin/MIRES commit: 065a0eb6f768635dcc8d2a16157c67ac4658e296 url: https://github.com/stephenSRMMartin/MIRES date-released: '2025-05-04' contact: - family-names: Martin given-names: Stephen email: stephenSRMMartin@gmail.com orcid: https://orcid.org/0000-0001-8085-2390