Tag Archives | Nonlinearities

Best Practices for Estimating, Interpreting, and Presenting Nonlinear Interaction Effects

Trenton D. Mize

Sociological Science, February 6, 2019
10.15195/v6.a4


Many effects of interest to sociologists are nonlinear. Additionally, many effects of interest are interaction effects—that is, the effect of one independent variable is contingent on the level of another independent variable. The proper way to estimate, interpret, and present these two types of effects individually are well known. However, many analyses that combine these two—that is, tests of interaction when the effects of interest are nonlinear—are not properly interpreted or tested. The consequences of approaching nonlinear interaction effects the way one would approach a linear interaction effect are severe and can often result in incorrect conclusions. I cover both nonlinear effects in the context of linear regression, and—most thoroughly—nonlinear effects in models for categorical outcomes (focusing on binary logit/probit). My goal in this article is to synthesize an evolving methodological literature and to provide straightforward advice and techniques to estimate,interpret, and present nonlinear interaction effects.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Trenton D. Mize: Department of Sociology and Advanced Methodologies, Purdue University
E-mail: tmize@purdue.edu

Acknowledgements: I thank J. Scott Long, Bianca Manago, Long Doan, and Josh Doyle for their helpful comments on previous drafts and Dave Armstrong and Shawn Bauldry for the many insightful conversations that influenced the content of the article.

  • Citation: Mize, Trenton D. 2019. “Best Practices for Estimating, Interpreting, and Presenting Non-linear Interaction Effects.” Sociological Science 6: 81-117.
  • Received: December 18, 2018
  • Accepted: December 27, 2018
  • Editors: Jesper Sørensen, Olav Sorenson
  • DOI: 10.15195/v6.a4


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