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modelbased: An R package to make the most out of your statistical models through marginal means, marginal effects, and model predictions

Makowski, D., Ben-Shachar, M. S., Wiernik, B. M., Patil, I., Thériault, R., & Lüdecke, D.

Journal of Open Source Software, 2025

modelbased is the easystats package for the step after fitting: estimated marginal means, marginal effects, contrasts and model predictions, for any supported model, so that what a model implies can be read off directly rather than reconstructed from its coefficients.

• DOI: 10.21105/joss.07969
• Full text (PDF)

Keywords: Software Development · Statistical Methods

Cite

Makowski, D., Ben-Shachar, M. S., Wiernik, B. M., Patil, I., Thériault, R., & Lüdecke, D. (2025). modelbased: An R package to make the most out of your statistical models through marginal means, marginal effects, and model predictions. Journal of Open Source Software. https://doi.org/10.21105/joss.07969

See also

• Check your outliers! An introduction to identifying statistical outliers in R with easystats — Thériault, R., Ben-Shachar, M. S., Patil, I., Lüdecke, D., Wiernik, B. M., & Makowski, D. (2024)
• Where Are We Going with Statistical Computing? From Mathematical Statistics to Collaborative Data Science — Makowski, D., & Waggoner, P. D. (2023)
• datawizard: An R Package for Easy Data Preparation and Statistical Transformations — Patil, I., Makowski, D., Ben-Shachar, M. S., Wiernik, B. M., Bacher, E., & Lüdecke, D. (2022)