4.8: Handling Missing Values
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There’s one last topic that I want to discuss briefly in this chapter, and that’s the issue of missing data. Real data sets very frequently turn out to have missing values: perhaps someone forgot to fill in a particular survey question, for instance. Missing data can be the source of a lot of tricky issues, most of which I’m going to gloss over. However, at a minimum, you need to understand the basics of handling missing data in SPSS.
Let’s start with the simplest case, in which you’re trying to calculate descriptive statistics for a single variable that has missing data. In SPSS, this means that there will be an empty cell in your data file:
Let’s assume that you want to calculate the mean of this variable. By default, SPSS will ignore any cases in which there is missing data. If we run Analyze/Descriptive Statistics/ Descriptives on var, the following output is produced:
Note that although there are four cases in the data set, only 3 are valid, so SPSS uses only the valid cases when computing the descriptive statistics. For our purposes here, that's really all you need to know.