Multiple Correspondence Analysis Output
The Output dialog box allows you to produce tables for object scores, discrimination measures, iteration history, correlations of original and transformed variables, category quantifications for selected variables, and descriptive statistics for selected variables.
Object scores. Displays the object scores, including mass, inertia, and contributions, and has the following options:
- Include Categories Of. Displays the category indicators of the analysis variables selected.
- Label Object Scores By. From the list of variables specified as labeling variables, you can select one to label the objects.
Discrimination measures. Displays the discrimination measures per variable and per dimension.
Iteration history. For each iteration, the variance accounted for, loss, and increase in variance accounted for are shown.
Correlations of original variables. Shows the correlation matrix of the original variables and the eigenvalues of that matrix.
Correlations of transformed variables. Shows the correlation matrix of the transformed (optimally scaled) variables and the eigenvalues of that matrix.
Category Quantifications and Contributions. Gives the category quantifications (coordinates), including mass, inertia, and contributions, for each dimension of the variable(s) selected.
Note: the coordinates and contributions (including the mass and inertia) are displayed in separate layers of the pivot table output, with the coordinates shown by default. To display the contributions, activate (double-click) on the table and select Contributions from the Layer dropdown list.
Descriptive Statistics. Displays frequencies, number of missing values, and mode of the variable(s) selected.
To Specify Multiple Correspondence Output
This feature requires the Categories option.
- From the menus choose:
- In the Multiple Correspondence Analysis dialog box, click Output.