SPSS Mult Response

The MULT RESPONSE command tabulates multiple-response sets.

Contents

SPSS Mult Response
1. Usage
2. Data Model

Usage

mult response /groups=FOOBARBAZ (foo to baz (1)) /frequencies=FOOBARBAZ.
mult response /groups=FOOBARBAZ "Foo, bar, and baz" (foo to baz (1)) /frequencies=FOOBARBAZ.

The /GROUPS subcommand defines the series of variables that represent a multiple-dichotomy group (nested within parentheses), as well as the value representing a selection (further nested within parentheses). The variable labels from each component variable become the value labels on the created table.

To define a multiple-response group, specify a range of values as (MIN,MAX). (This is useful if, for example, foo represents both a selection from a set as well as a category or rank.) The value labels from the first component variable become the value labels on the created table.

The optional label can be up to 40 characters long.

Variables

The /VARIABLES subcommand specifies numeric variables that should be additionally tabulated. This subcommand must follow the /GROUPS subcommand.

Variables must be specified with a range of valid values, so that the same number of cells can be allocated across the multiple-response set. The range is specified as (MIN,MAX).

mult response
  /groups=FOOBARBAZ (foo to baz (1))
  /variables=ham (1,2) spam eggs (1,5)
  /table=FOOBARBAZ by ham spam eggs.

Note that values are truncated to integers for all tabulations.

Frequencies

The /FREQUENCIES subcommand creates a tabulation. To tabulate any variable other than one created on the /GROUP subcommand, add a /VARIABLES subcommand first.

Tables

The /TABLES subcommand creates a cross-tabulation. To tabulate any variable other than a multiple response group, add a /VARIABLES subcommand first.

By default, when two multiple response groups are cross-tabulated, SPSS will tabulate each component variable in the first group by each component variable in the second group and sum the counts for each cell. In other words, responses are potentially counted multiple times.

If instead two multiple response groups should be pair-wise cross-tabulated, add the (PAIRED) option.

mult response /groups=FOOBARBAZ (foo to baz (1)) HAMSPAMEGGS (ham spam eggs (1))
  /tables=FOOBARBAZ by HAMSPAMEGGS (paired).

Cells

The default /CELLS subcommand is /CELLS=COUNT. This causes table cells to be populated with counts of observations.

Options are:

Name	Effect
`COUNT`	count
`ROW`	row percent
`COLUMN`	column percent
`TOTAL`	table percent
`ALL`	all of the above

If the /CELLS subcommand is specified without any options, the COUNT, ROW, COLUMN, and TOTAL options are selected automatically.

Missing

By default, SPSS will exclude observations with a user missing value for a tabulated variable even when the user missing value is included in the value range. Add the /MISSING=TABLE subcommand to explicitly allow this behavior, or add /MISSING=INCLUDE subcommand to disable it.

Add the /MISSING=MDGROUP subcommand to exclude cases with any missing values among the component variables of a multiple-dichotomy group.

Add the /MISSING=MCGROUP subcommand to exclude cases with any missing values among the component variables of a multiple-category group.

Base

By default, SPSS will use the number of observations included in a table as the base for computing percentages. This means that any respondent without a single response counted is excluded from the base.

If the PAIRED option is set, SPSS will instead use the number of responses counted the table as the base for computing percentages.

To explicitly use the first strategy, add the /BASE=CASES subcommand. To explicitly use the second strategy, add the /BASE=RESPONSES subcommand.

Data Model

The MULT RESPONSE command causes all pending transformations to execute, and reads the active dataset.

CategoryRicottone