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The `marginaleffects` package for `R`

marginaleffects allows users to compute and plot predictions, slopes, marginal means, and comparisons (contrasts, risk ratios, odds, etc.) for over 80 classes of statistical models. It can conduct linear and non-linear hypothesis tests, or equivalence tests, and calculate uncertainty estimates using the delta method, bootstrapping, or simulation-based inference.

The marginaleffects book (website) includes a “Get started” page, and over 25 chapters full of tutorials, case studies, and technical notes.

https://vincentarelbundock.github.io/marginaleffects

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Version

Install

install.packages('marginaleffects')

Monthly Downloads

60,808

Version

0.13.0

License

GPL (>= 3)

Maintainer

Vincent Arel-Bundock

Last Published

June 18th, 2023

Functions in marginaleffects (0.13.0)

get_model_matrix

Get a named model matrix

(EXPERIMENTAL) Bootstrap and Simulation-Based Inference

Get a named variance-covariance matrix from a model object (internal function)

marginaleffects

marginaleffects() is an alias to slopes()

Get predicted values from a model object (internal function)

marginal_means() is an alias to marginal_means()

(Non-)Linear Tests for Null Hypotheses, Joint Hypotheses, Equivalence, Non Superiority, and Non Inferiority

get_group_names

Get levels of the outcome variable in grouped or multivariate models

get_varcov_args

Take a summary() style vcov argument and convert it to insight::get_varcov()

posterior_draws

Extract Posterior Draws or Bootstrap Resamples from marginaleffects Objects

posteriordraws() is an alias to posterior_draws()

plot_comparisons

Plot Conditional or Marginal Comparisons

plot_predictions

Plot Conditional or Marginal Predictions

Plot Conditional or Marginal Slopes

meffects() is an alias to slopes()

plot_predictions() is an alias to plot_predictions()

plot_comparisons() is an alias to plot_comparisons()

plot_slopes() is an alias to plot_slopes()

print.marginaleffects

Print marginaleffects objects

Objects exported from other packages

Slopes (aka Partial derivatives, Marginal Effects, or Trends)

Internal function to set coefficients

sanitize_model_specific.glimML

Method to raise model-specific warnings and errors

expect_predictions

tinytest helper

tinytest helper

Average Estimates (aka "Margins")

Comparisons Between Predictions Made With Different Regressor Values

complete_levels

Create a data.frame with all factor or character levels

Get a named vector of coefficients from a model object (internal function)

expect_marginal_means

tinytest helper

tinytest helper

deltamethod() is an alias to hypotheses()