A Guided Interface for Mixed-Effects and Multilevel Models
mlmr-package.Rdmlmr provides a guided Shiny interface and supporting R toolkit for fitting, understanding, and reporting mixed-effects and multilevel models with lme4.
Details
The package is designed for users who want an HLM-style graphical workflow while preserving transparent and reproducible R code. The app supports level-based predictor selection, centering decisions, fixed effects, random intercepts, random slopes, interactions, model diagnostics, APA-style tables, level-by-level equations, combined equations, Tau variance-covariance displays, and reproducible exports.
Launch the app with run_mlmr().
Inspect the current production scope with
mlm_supported_models(). Inspect HLM-style parity and validation
evidence with mlm_hlm8_parity() and
mlm_validation_report().
Create manuscript and reproducibility materials with
mlm_publication_bundle().
To cite the package, use citation("mlmr").