GLM Multivariate Options
Optional statistics are available from this dialog box. Statistics are calculated using a fixedeffects model.
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 etasquared value for each effect and each parameter estimate. The etasquared 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 betweensubjects factors, for betweensubjects 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 betweensubjects factors. The spreadversuslevel 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 observedbypredictedbystandardized 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(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).
 Display

 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 etasquared value for each effect and each parameter estimate. The etasquared 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
 Displays the hypothesis and error SSCP matrices.
 Residual SSCP Matrix
 Displays the hypothesis and error 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 betweensubjects factors, for betweensubjects 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 betweensubjects factors.
 Spread vs. level plot
 Useful for checking assumptions about the data for investigating the assumption of equal variance. This item is disabled if there are no factors.
 Residual plot
 Produces an observedbypredictedbystandardized residuals plot for each dependent variable. The plot is useful for investigating the assumption of equal variance.
 Lack of fit
 Check 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 Multivariate
This feature requires SPSS® Statistics Standard Edition or the Advanced Statistics Option.
 From the menus choose:
 In the Multivariate dialog box, click Options.
You can select estimated marginal means for specific factors and interactions as well as other useful statistics.