# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "hlmLab" in publications use:' type: software license: MIT title: 'hlmLab: Hierarchical Linear Modeling with Visualization and Decomposition' version: 0.2.0.9000 doi: 10.32614/CRAN.package.hlmLab abstract: Provides functions for visualization and decomposition in hierarchical linear models (HLM) for applications in education, psychology, and the social sciences. Includes variance decomposition for two-level and three-level data structures following Snijders and Bosker (2012, ISBN:9781849202015), intraclass correlation (ICC) estimation and design effect computation as described in Shrout and Fleiss (1979) , and contextual effect decomposition via the Mundlak (1978) specification distinguishing within- and between-cluster components, with the uncertainty of the contextual contrast obtained from the full fixed-effect covariance matrix. Teaching displays cover simulated intraclass correlations, partial pooling of cluster means, random-slope heterogeneity, and cross-level interaction with an observed Level-2 moderator, following Hofmann and Gavin (1998) and Hamaker and Muthen (2020) . Multilevel models are estimated using 'lme4' (Bates et al., 2015 ). An optional 'Shiny' application enables interactive exploration of model components and parameter variation. The implementation follows the multilevel modeling framework of Raudenbush and Bryk (2002, ISBN:9780761919049). authors: - family-names: Hait given-names: Subir email: haitsubi@msu.edu orcid: https://orcid.org/0009-0004-9871-9677 repository: https://subirhait.r-universe.dev repository-code: https://github.com/subirhait/hlmLab commit: ff72875f981552fc8676f37c140de179dc83255c url: https://github.com/subirhait/hlmLab date-released: '2026-09-28' contact: - family-names: Hait given-names: Subir email: haitsubi@msu.edu orcid: https://orcid.org/0009-0004-9871-9677