A Practical Approach to Linear Mixed-Effects Modeling in R
A Linear Mixed-Effects Model (LMM) is a statistical model that combines both fixed effects and random effects to analyze data with repeated measurements or hierarchical structure. Let’s break down the key components and concepts of a Linear Mixed-Effects Model: 1) Fixed Effects: 2) Random Effects: 3) Linear Mixed-Effects Model Equation: The general equation of a Linear Mixed-Effects Model can be written as: Y= Xβ + Zb + ε 4) Estimation: In summary, Linear Mixed-Effects Models are a powerful statistical tool…