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mlmr 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().

To cite the package, use citation("mlmr").

Author

Marcus Harris