GLM Repeated Measures Options
Optional statistics are available from this dialog box. Statistics are calculated using a fixed-effects model.
- Display
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- 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 SPSS® Statistics Standard Edition or the Advanced Statistics Option.
- From the menus choose:
- Define your factors.
- 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.