Multiple Correspondence Analysis Results
Select an Input option and Variable(s) using the Multiple Correspondence Analysis (MCA) tab. Click the OK button in the Multiple Correspondence Analysis: Table Specifications Startup Panel to display the Multiple Correspondence Analysis Results dialog box, which contains four tabs:
Option | Description |
---|---|
Summary box | The
Summary box at the top of the dialog box shows the following:
The overall Chi-square value, the degrees of freedom, and associated p-value are only valid if the input table was an ordinary two-way table, which it is not. The number of factors that are retained for the spreadsheet of coordinates, and all plots of column points, is determined by the choice of options in the Number of dimensions group box on either the Quick tab or Options tab. To implement non-standard methods for standardizing the coordinates, click the Unstandardized matrices button on the Advanced tab, which reports the matrix of unstandardized generalized singular vectors from the singular value decomposition. The spreadsheet reporting those matrices can then be easily accessed using Statistica Visual Basic for any additional computations. |
Copy button | Copies either the selected text (if text has been selected) in the Summary box or all of the text (if no text has been selected) to the Clipboard. Note that the copied text retains formatting information (such as font, color, etc.). |
Contract/Expand button | Contracts or expands the
Summary box.
|
Summary | Displays a spreadsheet with the coordinates for the column points, as well as various additional statistics that are useful for evaluating the adequacy of the number of dimensions in the current solution. |
Cancel | Closes the Multiple Correspondence Analysis Results dialog box and returns to the Multiple Correspondence Analysis (MCA): Table Specifications Startup Panel. |
Options | Displays the Options menu. |
For details concerning the typical statistics computed in a multiple correspondence analysis and their interpretation refer to the MCA - Introductory Overview; see also Computational Details.