I'll try to explain the process of running a linear mixed effects model in MATLAB without diving too deep into coding details.

1. Prepare your data: First, you need to have your data ready in a file, such as a CSV (Comma Separated Values) file. This file should contain your variables (columns) and the observations (rows).
2. Import your data: MATLAB has tools that allow you to import your data file into its workspace, so you can work with it. This creates a table in MATLAB that contains your data.
3. Define your model: In a linear mixed effects model, there are two types of variables: fixed effects and random effects. Fixed effects are the main variables of interest in your model, while random effects account for the variation in your data due to different groups (e.g., different schools, different countries, etc.). You need to specify a formula that describes the relationship between your response variable (what you're trying to predict) and the fixed and random effects in your data.
4. Run the model: MATLAB provides a function called "fitlme" that takes your data and the model formula you defined and computes the linear mixed effects model for you. This function returns a model object that contains all the information about the fitted model.
5. Analyze the results: After fitting the model, you can use various functions and tools in MATLAB to analyze the results. This includes viewing the model coefficients, looking at the fixed and random effects, and performing hypothesis tests to assess the significance of the effects.

In summary, to run a linear mixed effects model in MATLAB, you need to import your data, define the model formula specifying fixed and random effects, run the model using the "fitlme" function, and then analyze the results using different methods provided by MATLAB.
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