# Linear Mixed Models Random Effects

This feature requires SPSS® Statistics Standard Edition or the Advanced Statistics Option.

**Covariance type.** This allows you to specify the covariance structure for the random-effects
model. A separate covariance matrix is estimated for each random effect.
The available structures are as follows:

- Ante-Dependence: First Order
- AR(1)
- AR(1): Heterogeneous
- ARMA(1,1)
- Compound Symmetry
- Compound Symmetry: Correlation Metric
- Compound Symmetry: Heterogeneous
- Diagonal
- Factor Analytic: First Order
- Factor Analytic: First Order, Heterogeneous
- Huynh-Feldt
- Scaled Identity
- Toeplitz
- Toeplitz: Heterogeneous
- Unstructured
- Unstructured: Correlation Metric
- Variance Components

See the topic Covariance Structures for more information.

**Random Effects.** There is no default model, so you must explicitly specify the random
effects. Alternatively, you can build nested or non-nested terms.
You can also choose to include an intercept term in the random-effects
model.

You can specify multiple random-effects models. After building the first model, click Next to build the next model. Click Previous to scroll back through existing models. Each random-effect model is assumed to be independent of every other random-effect model; that is, separate covariance matrices will be computed for each. Terms specified in the same random-effect model can be correlated.

**Subject Groupings.** The variables listed are those that you selected as subject variables
in the Select Subjects/Repeated Variables dialog box. Choose some
or all of these in order to define the subjects for the random-effects
model.

**Display parameter predictions for this set of random effects.** Specifies to display the
random-effects parameter estimates.