GLM Repeated Measures Options
Optional statistics are available from this dialog box. Statistics are calculated using a fixed-effects model.
Estimated Marginal Means. Select the factors and interactions for which you want estimates of the population marginal means in the cells. These means are adjusted for the covariates, if any. Both within-subjects and between-subjects factors can be selected.
- Compare main effects. Provides uncorrected pairwise comparisons among estimated marginal means for any main effect in the model, for both between- and within-subjects factors. This item is available only if main effects are selected under the Display Means For list.
- Confidence interval adjustment. Select least significant difference (LSD), Bonferroni, or Sidak adjustment to the confidence intervals and significance. This item is available only if Compare main effects is selected.
Display. Select Descriptive statistics to produce 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. Select Observed power to obtain the power of the test when the alternative hypothesis is set based on the observed value. Select Parameter estimates to produce the parameter estimates, standard errors, t tests, confidence intervals, and the observed power for each test. You can display the hypothesis and error SSCP matrices and the Residual SSCP matrix plus 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. The spread-versus-level and residual plots options are useful for checking assumptions about the data. This item is disabled if there are no factors. Select Residual plots to produce an observed-by-predicted-by-standardized residuals plot for each dependent variable. These plots are useful for investigating the assumption of equal variance. Select Lack of fit test to check if the relationship between the dependent variable and the independent variables can be adequately described by the model. General estimable function allows you to construct custom hypothesis tests based on the general estimable function. Rows in any contrast coefficient matrix are linear combinations of the general estimable function.
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 box.
Specifying Options for GLM Repeated Measures
This feature requires 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.