In order to understand how an axis becomes a variable, look at the different types of element you can have and see how they appear in the SPSS files. The simplest axis is one in which the elements are single-coded.

For example, the axis:

becomes:

In the axis, the element’s condition determines the code which represents the response in the data. In the variable, the values for each answer are determined solely by the element’s position in the axis. Thus, Not stated is the third answer so it becomes value 3 in the SPSS variable.

The base element is count of respondents in the axis rather than an answer so it is ignored.

nqtspss converts multicoded data into the standard SPSS format. When an axis is multicoded, nqtspss creates as many variables as there are elements in the axis. Each variable is named according to the axis name, but has a numeric suffix associated with the element’s position in the axis.

For example, the multicoded axis:

is converted into five variables named @color1 to @color5. The variable names start with @ indicating that they are derived variables rather than variables related directly to a Quantum axis. Each variable has two values: 1 if the respondent gave that answer, or 0 if they did not. The definition for @color1 is therefore:

A similar thing happens with numeric codings specified using the Quantum bit/fld statements. nqtspss creates a separate variable for each value on the bit/fld statement and inserts a 0 or 1 in the record depending on whether the respondent gave a particular answer.

For example:

is converted into two variables @cars1 and @cars2, each with 0/1 values.

Where the data is truly numeric (that is, numbers rather than numeric codes) the axis is treated as single-coded and the SPSS values are calculated according to the element’s position in the axis. Thus:

becomes:

An option is available to change the values assigned to each item.

If a respondent answers all questions in the questionnaire, the record will contain one value for each variable. If some questions are unanswered, or if filtering excludes a respondent from the axis, nqtspss inserts dummy (-99.99) values in the appropriate positions in the records. In SPSS, the same dummy value is used for all variables and is called the missing value.

Quantum runs can be weighted. In Quantum, weights (apart from pre- and postweights) are defined in the tab section. nqtspss converts the weighting matrix into a variable with a numeric suffix, and appends each respondent’s weight to the end of the record. Because the weight variable is not a bona fide Quantum axis, nqtspss starts the variable name with an @ sign. Thus, the statement:

appears at the end of the DATA LIST as @weight0, and records have either 100 or 200 as their last value, depending on whether the respondent is male or female.

If the run contains more than one weighting matrix, the second matrix is named @weight1, the third is named @weight2, and so on.

If you want to export data in numeric variables to SPSS, you need to create a namedinc statement for each numeric variable.

namedinc statements should be defined after any global titles but before your tab statements and are in the form:

The data_spec can be anything which gives an integer or float result.

If, however, a numeric variable called shop does not exist, you can define it by specifying which columns it refers to. It could, for example, be written as:

If you do not specify a variable name (varname=), Quantum sets the name to the variable’s data_spec. If you do not assign a description to the variable (vartext=), Quantum makes the description the same as its name.

Numeric variables do not have a predefined set of values, so there is no VALUE LABELS section. Instead, the exact value of the variable is placed on a new line underneath the record in the data file. A comment of the form:

is placed at the end of the file.