The Marginal Effects Zoo: A Guide to Interpretation Using marginaleffects for R

Human rights
Civil society
NGO regulations
COVID-19

Vincent Arel-Bundock, Noah Greifer, and Andrew Heiss, “The Marginal Effects Zoo: A Guide to Interpretation Using marginaleffects for R”

Authors
Affiliations

Université de Montréal

Institute for Quantitative Social Science, Harvard University

Andrew Young School of Policy Studies, Georgia State University

Published

February 2023

Abstract

Analysts often transform their models’ parameter estimates to report more meaningful and interpretable quantities of interest. This article presents a simple conceptual framework to describe a vast array of estimands which are reported under imprecise and inconsistent terminology across disciplines: predictions, marginal predictions, marginal means, marginal effects, conditional effects, slopes, contrasts, risk ratios, etc. We introduce marginaleffects, an R package which offers a simple and powerful interface to compute all of those quantites, and to conduct hypothesis tests on them. marginaleffects is lightweight; extensible; it works well in combination with other R packages; and it supports over 70 classes of models, including Generalized Linear, Generalized Additive, Mixed Effects, and Bayesian models.