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The marginaleffects package for R and Python offers a single point of entry to easily interpret the results of over 100 classes of models, using a simple and consistent user interface.

This package comes with a free full-length online book, with extensive tutorials: https://marginaleffects.com

The package’s benefits include:

To cite marginaleffects in publications use:

Arel-Bundock V, Greifer N, Heiss A (2024). “How to Interpret Statistical Models Using marginaleffects for R and Python.” Journal of Statistical Software, 111(9), 1-32.

A BibTeX entry for LaTeX users is

@Article{, title = {How to Interpret Statistical Models Using {marginaleffects} for {R} and {Python}}, author = {Vincent Arel-Bundock and Noah Greifer and Andrew Heiss}, journal = {Journal of Statistical Software}, year = {2024}, volume = {111}, number = {9}, pages = {1–32}, doi = {10.18637/jss.v111.i09}, }

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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