Multiple Correspondence Analysis Results - Review Tab

Select the Review tab of the

Multiple Correspondence Analysis Results

dialog box to access the options described here. Use these options to review the input table (click the Observed frequencies button), as well as various values computed based on the input table. Note that you can mark these results spreadsheets as input spreadsheets for subsequent analysis, for example, to use the Graphics options to produce graphical summaries of the results.

Option	Description
Observed frequencies	Displays a spreadsheet showing the input table (that is, Burt table).
Row percentages	Displays a spreadsheet showing the values in the input table after transformation to row percentages. The values in each row sum to 100%.
Column percentages	Displays a spreadsheet showing the values in the input table after transformation to column percentages. The values in each column sum to 100%.
Total percentages	Displays a spreadsheet showing the values in the input table after transformation to percentages of the total sum of all values. The sum of all values in the table equals to 100%.
Expected (chi-square)	Displays a spreadsheet with the expected values under the hypothesis that the row and column variables are independent of each other. Note that since the input table is a Burt table, these values are usually not of interest in a multiple correspondence analysis.
Observed minus expected	Displays a spreadsheet with the differences between the observed table values and the expected values.
Contribution to chi-square	Displays a spreadsheet with the respective cells' contributions to the overall Chi-square value (note that these values are only valid if the input table was a standard two-way table, and not a Burt table). For example, for row i and column j this value is computed as: (observed value - expected value)² /expected value. The sum of all values is equal to the overall Chi-square value.
Standardized deviates	Displays a spreadsheet whose standardized deviate values are computed as the square-root of the contribution to Chi-square values.