Use Fit Mixed Effects Model to fit a model when you have a continuous response, at least 1 random factor, and optional fixed factors and covariates. The model can include main effect terms, crossed terms, and nested terms as defined by the factors and the covariates. You can also include polynomial terms of the covariates.

For example, a quality team for a hospital network wants to study a new setup procedure for operating rooms. The goal is to decrease the number of minutes after the scheduled time for a surgery that the surgery actually begins. The team decides that to study the new procedure at all of the hospitals in the network would take too much time and coordination. Instead, the team selects a random sample of hospitals for the study. For the analysis, the hospital where the study occurs is a specific level of the random factor, Hospital. Whether a surgery uses the old procedure or the new procedure is a fixed factor.

After you perform the analysis, Minitab stores the model so that you can do any of the following analyses:

- Compare group means.
- Predict the response for new observations.
- Use factorial and interaction plots to compare means.

To fit a mixed effects model, choose

If you do not have any random factors, use Fit General Linear Model. For more information on random factors, go to What is the difference between fixed and random factors?.