The Explore Missing Values utility provides several ways to identify and understand the missing values in your data. It also provides methods for conducting multivariate normal imputation for missing values. These methods assume that data are missing at random, which means that the probability that an observation is missing depends only on the values of the other variables in the study. If you suspect that missing values are not missing at random, then consider using the Informative Missing procedure, which is available in a number of platforms. For more information, see Informative Missing in the Fitting Linear Models book.