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.