Categorical Principal Components Analysis Missing Values

Use the Missing Values dialog box to choose the strategy for handling missing values in analysis variables and supplementary variables.

Strategy. Choose to exclude missing values (passive treatment), impute missing values (active treatment), or exclude objects with missing values (listwise deletion).

• Exclude missing values; for correlations impute after quantification. Objects with missing values on the selected variable do not contribute to the analysis for this variable. If all variables are given passive treatment, then objects with missing values on all variables are treated as supplementary. If correlations are specified in the Output dialog box, then (after analysis) missing values are imputed with the most frequent category, or mode, of the variable for the correlations of the original variables. For the correlations of the optimally scaled variables, you can choose the method of imputation.
  • Mode. Replace missing values with the mode of the optimally scaled variable.
  • Extra category. Replace missing values with the quantification of an extra category. This setting implies that objects with a missing value on this variable are considered to belong to the same (extra) category.
  • Random category. Impute each missing value on a variable with the quantified value of a different random category number based on the marginal frequencies of the categories of the variable.
• Impute missing values. Objects with missing values on the selected variable have those values imputed. You can choose the method of imputation.
  • Mode. Replace missing values with the most frequent category. When there are multiple modes, the one with the smallest category indicator is used.
  • Extra category. Replace missing values with the same quantification of an extra category. This setting implies that objects with a missing value on this variable are considered to belong to the same (extra) category.
  • Random category. Replace each missing value on a variable with a different random category number based on the marginal frequencies of the categories.
• Exclude objects with missing values on this variable. Objects with missing values on the selected variable are excluded from the analysis. This strategy is not available for supplementary variables.

To Specify CATPCA Missing Values

This feature requires the Categories option.

1. From the menus, choose:

   Analyze > Dimension Reduction > Optimal Scaling...

2. In the Categorical Principal Components dialog box, click Missing.