In Database Multiple Regression: Specifications Advanced Tab
In the In-Database Multiple Regression node dialog box, under the Specifications heading, select the Advanced tab to access the following options.
Summary: Regression results. Select this check box to produce two spreadsheets. The Summary Statistics spreadsheet displays the summary statistics for the regression analysis (e.g., R, R-square, etc.). The Regression Summary for Dependent Variable spreadsheet displays the standardized (Beta) and non-standardized (B) regression coefficients (weights), their standard error, and statistical significance. The Beta coefficients are the coefficients you would have obtained had you first standardized all of your variables to a mean of 0 and a standard deviation of 1. Thus, the magnitude of these Beta coefficients allow you to compare the relative contribution of each independent variable in the prediction of the dependent variable.
| Element Name | Description |
|---|---|
| Summary: Correlations | Select this check box to produce a spreadsheet containing the correlation matrix for the selected variables. |
| Partial correlations | Select this check box to produce a spreadsheet with:
The beta in (standard regression coefficient for the respective variable if it were to enter into the regression equation as an independent variable); The partial correlation (between the respective variable and the dependent variable, after controlling for all other independent variables in the equation); The semi-partial (part) correlation (the correlation between the unadjusted dependent variable with the respective variable after controlling for all independent variables in the equation; matrices of partial correlations and semi-partial (or part) correlations can be computed in the General Linear Model (GLM) and General Regression Models (GRM) modules); The tolerance for the respective variable (defined as 1 minus the squared multiple correlation between the respective variable and all independent variables in the regression equation); The R-square (between the current variable and all other variables in the regression equation); The t-value associated with these statistics for the respective variable, and The statistical significance of the t-value. These statistics will first be displayed separately for variables not currently in the regression equation, and for the variables in the regression equation (if any). ANOVA (Overall goodness of fit). Select this check box to produce a spreadsheet with a complete Analysis of Variance table for the current regression equation. |
| Redundancy | Select this check box to produce a spreadsheet with various indicators of the redundancy of independent variables (currently included or not included in the equation). Specifically, for each variable, the spreadsheet will show 1) the tolerance (defined as 1 - R-square for the respective variable with all other variables currently in the equation), 2) the R-square (between the current variable and all other variables in the regression equation, 3) the partial correlation (between the respective variable and the dependent variable, after controlling for all other independent variables in the equation), and 4) the semi-partial (part) correlation (the correlation between the unadjusted dependent variable with the respective variable after controlling for all independent variables in the equation). |
| Options / W | See Common Options. |