An introduction to linear mixed effects modeling in R

This tutorial serves as both an approachable theoretical introduction to mixed effects modeling and a practical introduction to how to implement these models in R. The intended audience is any researcher who has 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 paper, 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, as well as the data and R script used to build the models described in the text 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 models in their own research.