19/06/2017
SPSS term of the week: Missing Values.
Missing Values defines specified data values as user-missing. For example, you might want to distinguish between data that are missing because a respondent refused to answer and data that are missing because the question didn't apply to that respondent. Data values that are specified as user-missing are flagged for special treatment and are excluded from most calculations.
• User-missing value specifications are saved with the data file. You do not need to redefine user-missing values each time you open the data file.
• You can enter up to three discrete (individual) missing values, a range of missing values, or a range plus one discrete value.
• Ranges can be specified only for numeric variables.
• All string values, including null or blank values, are considered to be valid unless you explicitly define them as missing.
• Missing values for string variables cannot exceed eight bytes. (There is no limit on the defined width of the string variable, but defined missing values cannot exceed eight bytes.)
• To define null or blank values as missing for a string variable, enter a single space in one of the fields under the Discrete missing values selection.
