To run a linear mixed effects model in MATLAB, you can use the "fitlme" function from the Statistics and Machine Learning Toolbox. Here's an example of how to use this function:

```matlab
% Load sample data
load hospital;

% Define model formula
formula = 'Age ~ BloodPressure + (1|Hospital)';

% Fit linear mixed effects model
lme = fitlme(hospital, formula);

% Display model summary
disp(lme);

% Plot residuals vs. fitted values
plotResiduals(lme);
```

In this example, we are fitting a linear mixed effects model to the "hospital" dataset, which is included in MATLAB as a sample dataset. The model formula specifies that we are modeling "Age" as a function of "BloodPressure", with random intercepts for each "Hospital". The "fitlme" function estimates the model parameters and returns a "LinearMixedModel" object, which can be used to extract model coefficients, residuals, and other information. The "plotResiduals" function can be used to visualize the residuals of the model to check for any systematic patterns.

Note that the "fitlme" function allows for a wide range of model specifications, including different covariance structures, fixed and random effects, and interactions. You may need to adjust the formula and other options depending on your specific research question and data.
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