Multiple Response Define Sets

The Define Multiple Response Sets procedure groups elementary variables into multiple dichotomy and multiple category sets, for which you can obtain frequency tables and crosstabulations. You can define up to 20 multiple response sets. Each set must have a unique name. To remove a set, highlight it on the list of multiple response sets and click Remove. To change a set, highlight it on the list, modify any set definition characteristics, and click Change.

You can code your elementary variables as dichotomies or categories. To use dichotomous variables, select Dichotomies to create a multiple dichotomy set. Enter an integer value for Counted value. Each variable having at least one occurrence of the counted value becomes a category of the multiple dichotomy set. Select Categories to create a multiple category set having the same range of values as the component variables. Enter integer values for the minimum and maximum values of the range for categories of the multiple category set. The procedure totals each distinct integer value in the inclusive range across all component variables. Empty categories are not tabulated.

Each multiple response set must be assigned a unique name of up to seven characters. The procedure prefixes a dollar sign ($) to the name you assign. You cannot use the following reserved names: casenum, sysmis, jdate, date, time, length, and width. The name of the multiple response set exists only for use in multiple response procedures. You cannot refer to multiple response set names in other procedures. Optionally, you can enter a descriptive variable label for the multiple response set. The label can be up to 40 characters long.

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To Define Multiple Response Sets

1. From the menus choose:

   Analyze > Multiple Response > Define Variable Sets...

2. Select two or more variables.
3. If your variables are coded as dichotomies, indicate which value you want to have counted. If your variables are coded as categories, define the range of the categories.
4. Enter a unique name for each multiple response set.
5. Click Add to add the multiple response set to the list of defined sets.

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.

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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

1. From the menus choose:

   Analyze > Multiple Response > Frequencies...

2. Select one or more multiple response sets.

Multiple Response Crosstabs

The Multiple Response Crosstabs procedure crosstabulates defined multiple response sets, elementary variables, or a combination. You can also obtain cell percentages based on cases or responses, modify the handling of missing values, or get paired crosstabulations. You must first define one or more multiple response sets (see "To Define Multiple Response 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. The procedure displays category labels for columns on three lines, with up to eight characters per line. To avoid splitting words, you can reverse row and column items or redefine labels.

Example. Both multiple dichotomy and multiple category sets can be crosstabulated with other variables in this procedure. An airline passenger survey asks passengers for the following information: Circle all of the following airlines you have flown at least once in the last six months (American, United, TWA). Which is more important in selecting a flight--schedule or service? Select only one. After entering the data as dichotomies or multiple categories and combining them into a set, you can crosstabulate the airline choices with the question involving service or schedule.

Statistics. Crosstabulation with cell, row, column, and total counts, and cell, row, column, and total percentages. The cell percentages can be based on cases or responses.

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Multiple Response Crosstabs Data Considerations

Data. Use multiple response sets or numeric categorical variables.

Assumptions. The counts and percentages provide a useful description of data from any distribution.

Related procedures. The Multiple Response Define Sets procedure allows you to define multiple response sets.

To Obtain Multiple Response Crosstabs

1. From the menus choose:

   Analyze > Multiple Response > Crosstabs...

2. Select one or more numeric variables or multiple response sets for each dimension of the crosstabulation.
3. Define the range of each elementary variable.