GLM Repeated Measures Model

Specify Model. A full factorial model contains all factor main effects, all covariate main effects, and all factor-by-factor interactions. It does not contain covariate interactions. Select Build terms to specify only a subset of interactions or to specify factor-by-covariate interactions. You must indicate all of the terms to be included in the model. Select Build custom terms to include nested terms or when you want to explicitly build any term variable by variable.

Between-Subjects. The between-subjects factors and covariates are listed. Nesting for repeated measures is limited to between-subjects factors.
Note: There is no option to specify the within-subjects design because the multivariate general linear model that is fitted, when you specify repeated measures, always includes all possible within-subjects factor interactions.

Between-Subjects Model. The model depends on the nature of your data. After selecting Build terms, you can select the between-subjects effects and interactions that are of interest in your analysis.

Sum of squares. The method of calculating the sums of squares for the between-subjects model. For balanced or unbalanced between-subjects models with no missing cells, the Type III sum-of-squares method is the most commonly used.

Obtaining Models for GLM Repeated Measures

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

  1. From the menus choose:

    Analyze > General Linear Model > Repeated Measures...

  2. Define your factors.
  3. In the Repeated Measures dialog box, click Model.
  4. In the Repeated Measures Model dialog box, select Build terms.
  5. Select one or more between-subjects factors.
  6. Select a method for building the terms and then move the between-subjects factors.
  7. Repeat these steps for between-subjects factors and covariates until you have the model you want. The interaction of each between-subjects term with each within-subjects term is automatically included in the model. That is, if W is a within-subjects factor in the model and B is a between-subjects factor in the model, W*B will be in the model.

Optionally, you can change the type of sum of squares.

Do not use the same term more than once in the model.