An Introduction to Linear Mixed-Effects Modeling in R

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  • Violet A. Brown
    Department of Psychological & Brain Sciences, Washington University in St. Louis

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<jats:p> 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. </jats:p>

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