IBM SPSS Modeler Essentials

Ways to address missing data

There are three ways to address missing data:

• Remove fields
• Remove cases
• Impute missing values

It can be necessary at times to remove fields with a large proportion of missing values. The easiest way to remove fields is to use a Filter node (discussed later in the book), however you can also use the Data Audit node to do this.

Note that in some cases missing data can be predictive of behavior, so it is important to assess the importance of a variable before removing a field.

In some situations, it may be necessary to remove cases instead of fields. For example, you may be developing a predictive model to predict customers' purchasing behavior and you simply do not have enough information concerning new customers. ...