Variable name. Each variable in the dataset has been assigned a unique name, which is preceded by the letter "V"
(for variable). The variable names run from V001 to V189. Note that each variable name always has three digits
(e.g., V002, not V2). You should use these variable names when you specify variables in the SDA dialog boxes.
Variable label. Each variable has been given a unique label. These labels provide a brief description of what the
variable refers to (e.g., the label for V002 is "Presidential vote"). Because there are maximum allowable lengths for
these variable labels, they sometimes have an abbreviated form.
Text of question or description of variable. An explanation of the meaning of each variable is provided by an
approximate description of the question asked or a general description of the variable. For example, the question
text for V002 is "Whom did you vote for in the presidential election?"
Value codes and value labels. The possible values for each variable are given in the codebook. Both the numeric codes
and a brief explanation of what the codes refer to are provided. Because there are maximum allowable lengths for these labels,
they often have an abbreviated form. For example, V002 has three valid codes. A a code of "1" indicates a vote for Obama,
a code of "2" indicates a vote for McCain, and a code of "3" indicates a vote for another candidate, such as Bob Barr.
Additionally, a code of "9" is used for respondents who do not fit into any of these categories. For this last group of
respondents we have only "missing data." Missing data occurs because: (a) the question does not apply to the
respondent--e.g., people who did not vote were not asked which presidential candidate they voted for; (b) the
respondent refused to give a response or had no opinion; or (c) the interviewer failed to obtain or record the
information for some other reason. The label "NA" is attached to this category to indicate that the item is "not
applicable" or that the information was "not ascertained."
Frequencies. To the left of the value descriptions and codes is a set of numbers called the frequencies (or
marginals or marginal frequencies). The frequencies or marginals indicate the total number of respondents who fall
into each category of the variable. These frequencies are based on the unweighted data (see the discussion on
weighting). Although the codebook frequencies are based on the unweighted data, any analysis
that is conducted should use the weighted data. For this reason, there may be some discrepancies between the codebook
information and the tables generated in your analysis. In order to view the frequencies based on the weighted data,
select the "Run frequencies..." option in SDA and enter the name of the variable for which you desire weighted frequencies.
Even though the differences between the unweighted and weighted frequencies can be large, you can obtain a good general idea
of the distribution of responses for any variable by viewing the codebook information.
Marginal percentages. Besides providing the number of respondents who fall into each category for every variable, the
codebook also provides the percentage breakdown for these marginal frequencies. There are two columns of percentages. The
first column is based only on the valid responses for the variable (i.e., missing data are excluded). The second column is
based on all responses, including the missing data category.