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 …