Multiple Response Frequencies
The Multiple Response Frequencies procedure produces frequency tables for multiple response sets. You must first define one or more multiple response sets (see "Multiple Response Define Sets").
For multiple dichotomy sets, category names shown in the output come from variable labels defined for elementary variables in the group. If the variable labels are not defined, variable names are used as labels. For multiple category sets, category labels come from the value labels of the first variable in the group. If categories missing for the first variable are present for other variables in the group, define a value label for the missing categories.
Missing Values. Cases with missing values are excluded on a table-by-table basis. Alternatively, you can choose one or both of the following:
- Exclude cases listwise within dichotomies. Excludes cases with missing values for any variable from the tabulation of the multiple dichotomy set. This applies only to multiple response sets defined as dichotomy sets. By default, a case is considered missing for a multiple dichotomy set if none of its component variables contains the counted value. Cases with missing values for some (but not all variables) are included in the tabulations of the group if at least one variable contains the counted value.
- Exclude cases listwise within categories. Excludes cases with missing values for any variable from tabulation of the multiple category set. This applies only to multiple response sets defined as category sets. By default, a case is considered missing for a multiple category set only if none of its components has valid values within the defined range.
Example. Each variable created from a survey question is an elementary variable. To analyze a multiple response item, you must combine the variables into one of two types of multiple response sets: a multiple dichotomy set or a multiple category set. For example, if an airline survey asked which of three airlines (American, United, TWA) you have flown in the last six months and you used dichotomous variables and defined a multiple dichotomy set, each of the three variables in the set would become a category of the group variable. The counts and percentages for the three airlines are displayed in one frequency table. If you discover that no respondent mentioned more than two airlines, you could create two variables, each having three codes, one for each airline. If you define a multiple category set, the values are tabulated by adding the same codes in the elementary variables together. The resulting set of values is the same as those for each of the elementary variables. For example, 30 responses for United are the sum of the five United responses for airline 1 and the 25 United responses for airline 2. The counts and percentages for the three airlines are displayed in one frequency table.
Statistics. Frequency tables displaying counts, percentages of responses, percentages of cases, number of valid cases, and number of missing cases.
Multiple Response Frequencies Data Considerations
Data. Use multiple response sets.
Assumptions. The counts and percentages provide a useful description for data from any distribution.
Related procedures. The Multiple Response Define Sets procedure allows you to define multiple response sets.
To Obtain Multiple Response Frequencies
- From the menus choose:
- Select one or more multiple response sets.