GLM Repeated Measures Options

Optional statistics are available from this dialog box. Statistics are calculated using a fixed-effects model.

Descriptive statistics
Produces observed means, standard deviations, and counts for all of the dependent variables in all cells.
Estimates of effect size
Gives a partial eta-squared value for each effect and each parameter estimate. The eta-squared statistic describes the proportion of total variability attributable to a factor.
Observed power
Obtains the power of the test when the alternative hypothesis is set based on the observed value.
Parameter estimates
Produces the parameter estimates, standard errors, t tests, confidence intervals, and the observed power for each test.
SSCP matrices
Display the hypothesis and error SSCP matrices.
Residual SSCP matrix
Displays the Residual SSCP matrix.
Transformation Matrix
Displays Bartlett's test of sphericity of the residual covariance matrix.
Homogeneity tests
Produces the Levene test of the homogeneity of variance for each dependent variable across all level combinations of the between-subjects factors, for between-subjects factors only. Also, homogeneity tests include Box's M test of the homogeneity of the covariance matrices of the dependent variables across all level combinations of the between-subjects factors.
Spread vs. level plot
Useful for checking assumptions about the data. This option is disabled if there are no factors.
Residual plot
Produces an observed-by-predicted-by-standardized residuals plot for each dependent variable. These plots are useful for investigating the assumption of equal variance. This option is disabled if there are no factors.
Lack of fit
Checks if the relationship between the dependent variable and the independent variables can be adequately described by the model.
General estimable function(s)
Allows you to construct custom hypothesis tests based on the general estimable function(s). Rows in any contrast coefficient matrix are linear combinations of the general estimable function(s).
Significance level
You might want to adjust the significance level used in post hoc tests and the confidence level used for constructing confidence intervals. The specified value is also used to calculate the observed power for the test. When you specify a significance level, the associated level of the confidence intervals is displayed in the dialog.

Specifying Options for GLM Repeated Measures

This feature requires Custom Tables and Advanced Statistics.

  1. From the menus choose:

    Analyze > General Linear Model > Repeated Measures...

  2. Define your factors.
  3. In the Repeated Measures dialog box, click Options.

You can request estimated marginal means for specific factors and interactions as well as other useful statistics.