Select the Summary tab of the GLM More Results or the ANOVA More Results dialog box to access options to display the main results for the current analysis. Depending on the type of design, whether random effects are present in the design, whether there are categorical predictor variables in the design, and/or whether there are within-subject (repeated measures) in the design, some of the options described below may not be available on the Summary tab.

If you select Huge balanced ANOVA on the GLM Startup Panel - Quick tab, or specify SSTYPE=BALANCED in the GLM syntax, then several advanced options are not available in the results dialog box (due to the computational shortcuts employed in order to efficiently analyze huge balanced designs; see also Balanced ANOVA in the Introductory Overview for details).

All
effects/Graphs.

Test all effects. Click the Test all effects button to display a spreadsheet with the ANOVA (MANOVA) table for all effects. If the design is univariate in nature (involves only a single dependent variable), then the univariate results ANOVA table will be displayed; the univariate results ANOVA table is also displayed for univariate repeated measures designs (where appropriate, multivariate tests for repeated measures can be computed via the Within effects options, see below); if the design is multivariate in nature, then the multivariate results MANOVA table will be displayed, showing the statistics as selected in the Multivariate tests, see below; if the design includes random effects and multiple dependent variables, then multiple univariate ANOVA tables (spreadsheets) will be displayed, one for each dependent variable (in that case, the tests reported in the ANOVA table will use synthesized error terms). For a discussion of the different types of designs, and how the respective ANOVA/MANOVA tables are computed, see the Introductory Overview.

Effect sizes. Click the Effect sizes button to display a spreadsheet with the ANOVA (MANOVA) table for all effects and the effect sizes and powers (i.e., Partial eta-squared, Non-centrality, and Observed power). Partial eta-squared is the proportion of the variability in the dependent variables that is explained by the effect. The Non-centrality value is the main statistic used to compute power, and the Power column contains the power values of the significant test on the effect. The ANOVA (MANOVA) table is described above, see Test all effects.

Univariate results. Click the Univariate results button to display a spreadsheet with the standard univariate ANOVA table for each dependent variable, regardless of whether or not the design includes within-subject (repeated measures factors). To review the univariate results for the within-subject design, use option Univ. tests in the Within effects box (see below).

Descriptive cell statistics. Click the Descriptive cell statistics button to display a spreadsheet of the descriptive statistics for each cell in the design; specifically, descriptive statistics are computed for the dependent variables, as well as any continuous predictors (covariates) in the design, for each column of the overparameterized design matrix for categorical effects. Thus, marginal means and standard deviations are available for each categorical effect in the design. Note that for lower-order effects (e.g., main-effects in designs that also contain interactions involving the main effects), the reported means are weighted marginal means, and as such estimates of the weighted population marginal means (for details, see, for example, Milliken and Johnson, 1984, page 132; see also the discussion of means in the description of the options on the Means tab). Least squares means (e.g., see Searle, 1987) can be computed on the Means tab, or via the All effects/Graphs option (see above); usually, in factorial designs, it is the least squares means that should be reviewed when interpreting significant effects from the ANOVA or MANOVA.

Between effects. The options in the Between effects group box allow you to review, as appropriate for the given design, various results statistics for the between-group design such as Design terms, Whole model R, Coefficients, and Estimate. For specific details on these tests/options, see Summary results for between effects in GLM and ANOVA.

Alpha values. Use the Alpha values group box to specify Confidence limits and Significance level values. These values are used in all results spreadsheets and graphs whenever a confidence limit is to be computed or a particular result is to be highlighted based its statistical significance.

Conf. Enter the value to be used for constructing confidence limits in the respective results spreadsheets or graphs (e.g., spreadsheet of parameter estimates, graph of means) in the Conf. field. By default 95% confidence limits will be constructed.

Signif. Enter the value to be used for all spreadsheets and graphs where statistically significant results are to be highlighted (e.g., in the All effects spreadsheet) in the Signif. field. By default all results significant at the p<.05 level will be highlighted.

Within effects. The options in the Within effects group box allow you to review, as appropriate for the given design, various results statistics for the within-subject (repeated measures) design such as Multivariate tests, G-G and H-F tests, Error SSCPs, Univariate tests, Sphericity test, Error Corrs, and Effect SSCPs. For specific details on these tests/options, see Summary results for within effects in GLM and ANOVA. If the current design does not include within-subject (repeated measures) factors, these options are not displayed on this tab.

Random effects. The options in the Random effects group box allow you to display the results related to the analysis of the random effects in the model such as Variance components, Expected MSs, Bar plot, Pie chart, and Denominator synthesis. For specific details on these tests/options, see Summary results for random effects in GLM.

Multivariate tests. In the Multivariate tests group box you can select the specific multivariate test statistics that are to be reported in the respective results spreadsheets. For descriptions of the different multivariate tests statistics, refer to the GLM Introductory Overview topic Multivariate Designs. These options are only available if the current design is multivariate in nature, i.e., if there are multiple dependent measures, or a within-subject (repeated measures) design with effects that have more than 2 levels (and hence, multivariate tests for those effects can be computed).

See also GLM - Index.