GRM Results - Quick Tab

Select the Quick tab of the GRM Results dialog to access options to display the main results for the current analysis. Depending on the type of design, whether or not there are categorical predictor variables in the design, or whether or not the current analysis is based on stepwise or best subset model building methods, some of the options described below may not be available on the Quick tab.

Element Name Description
All effects/G Click the All effects/G button to display the Table of All Effects dialog. This dialog shows the summary ANOVA (MANOVA) table for all effects; you can then select an effect and produce a spreadsheet or graph of the observed unweighted, observed weighted, and least squares means. Refer also to the description of the options on the Means tab for details concerning the different means computed by STATISTICA, and their standard errors. This option is only available if the current design includes categorical predictor variables.
All effects Click the 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; if the design is multivariate in nature, then the multivariate results MANOVA table will be displayed, showing the statistics as selected in the Multiv. tests group box on the GRM Results - Summary tab. 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 All effects.
Coefficients Click the Coefficients button to display a spreadsheet of the current parameter estimates (B), standardized parameter estimates (Beta), their standard errors, significance levels, and related statistics. In complex or incomplete designs, a Comment column may also be shown in the spreadsheet. The cells in this column may either be blank, or contain the designations Biased, Zeroed, or Dropped.
Biased parameters Whenever during the initial computations of the generalized inverse of the variance/covariance matrix of the design matrix (see GLM Introductory Overview) a column is found to be redundant, it is zeroed out (i.e., all elements in the variance/covariance matrix for that column are set to zero; this check is performed during the so-called sweeping operation, where the diagonal elements are checked against a small constant Delta; as specified via the SDELTA keyword or in the Sweep delta field on the Quick Specs Dialog - Options tab). Whenever a column in the design matrix is thus dropped from the analysis, the parameter estimates for the remaining columns belonging to the same effect are biased, because different orderings of the factor levels or columns in the design matrix for the respective effect will yield different parameter estimates for the respective columns. Thus, those parameter estimates are labeled as Biased in the Coefficients spreadsheet.
Zeroed Parameters labeled as Zeroed indicate that the respective columns in the design matrix are completely redundant with other columns in the design matrix, and hence, those columns were "dropped" or "zeroed out" from the design matrix. Usually, the parameter estimates for the remaining columns in the design matrix belonging to the same effect (as the one from which a column was zeroed) are labeled as Biased (see the description in the previous paragraph for additional details).
Pooled This designation is only used in conjunction with the stepwise or best subset regression model building method. Pooled effects are those that were excluded from the final model because they did not qualify for inclusion given the current model building method and criteria for inclusion. Refer to Model building in GRM in the Introductory Overview for a description of the stepwise and best subset regression methods.
Pareto Click the Pareto button to produce a Pareto chart of the parameter estimates (Coefficients, see above), or, optionally, the t-values associated with the parameter estimates if the t-vals check box is selected (see below). The Pareto chart shows the parameter estimates (or t-values) sorted by their absolute size. If you plot the t-values, a vertical line will also be shown to indicate the minimum magnitude of statistically significant parameter estimates, given the current criterion of statistical significance (specified in the Alpha values group box on the GRM Results - Summary tab). The Pareto chart is very useful for reviewing a large number of parameters.
t-vals Select the t-vals check box to display the absolute values of the t-values associated with the parameter estimates in the Pareto chart (see above); the Pareto chart will also include a vertical line to indicate the minimum magnitude of statistically significant parameter estimates, given the current criterion of statistical significance (specified in the Alpha values group box on the GRM Results - Summary tab).
Model building results The options in the Model building results group box will display summary spreadsheets for the stepwise regression analysis or the best subset regression analysis respectively. Please see Model building results in GRM for further details on these options. Refer also to Model building in GRM in the Introductory Overview for details concerning the available model building procedures.

See also GRM - Index.