An Introduction to Linear Mixed-Effects Modeling in R

• Published in: Advances in methods and practices in psychological science Vol. 4; no. 1
• Main Author: Brown, Violet A.
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.01.2021
• Subjects: R; language; speech perception; mixed-effects modeling; open data
• ISSN: 2515-2459; 2515-2467
• DOI: 10.1177/2515245920960351

This Tutorial serves as both an approachable theoretical introduction to mixed-effects modeling and a practical introduction to how to implement mixed-effects models in R. The intended audience is researchers who have some basic statistical knowledge, but little or no experience implementing mixed-effects models in R using their own data. In an attempt to increase the accessibility of this Tutorial, I deliberately avoid using mathematical terminology beyond what a student would learn in a standard graduate-level statistics course, but I reference articles and textbooks that provide more detail for interested readers. This Tutorial includes snippets of R code throughout; the data and R script used to build the models described in the text are available via OSF at https://osf.io/v6qag/, so readers can follow along if they wish. The goal of this practical introduction is to provide researchers with the tools they need to begin implementing mixed-effects models in their own research.