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

R Submitted 10 March 2025 • Published 30 May 2025
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Authors

Dominique Makowski (0000-0001-5375-9967), Mattan S. Ben-Shachar (0000-0002-4287-4801), Brenton M. Wiernik (0000-0001-9560-6336), Indrajeet Patil (0000-0003-1995-6531), Rémi Thériault (0000-0003-4315-6788), Daniel Lüdecke (0000-0002-8895-3206)

Citation

Makowski et al., (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, 10(109), 7969, https://doi.org/10.21105/joss.07969

@article{Makowski2025, doi = {10.21105/joss.07969}, url = {https://doi.org/10.21105/joss.07969}, year = {2025}, publisher = {The Open Journal}, volume = {10}, number = {109}, pages = {7969}, author = {Dominique Makowski and Mattan S. Ben-Shachar and Brenton M. Wiernik and Indrajeet Patil and Rémi Thériault and Daniel Lüdecke}, title = {modelbased: An R package to make the most out of your statistical models through marginal means, marginal effects, and model predictions}, journal = {Journal of Open Source Software} }
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easystats marginal effects marginal means model predictions emmeans

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This work is licensed under a Creative Commons Attribution 4.0 International License.

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Journal of Open Source Software is part of Open Journals, which is a NumFOCUS-sponsored project.

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ISSN 2475-9066