By default, SAS Visual Statistics handles missing values by dropping all observations that contain a missing value in any assigned role variable. However, the Linear Regression, Logistic Regression, and Generalized Linear Model models provide the Informative missingness property. In some cases, the fact that an observation contains a missing value provides relevant modeling information. Selecting this property
explicitly models missing values of variables as a separate variable. For measure
variables, missing values are imputed with the observed mean, and an indicator variable is created to denote missingness. For category variables, missing values are considered a distinct level.