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.