If one of the scoring variables in the DATA= data set has a missing value for an observation, all the scores have missing values for that observation. The exception to this criterion is that if the PREDICT option is specified, the variable with a coefficient of –1 can tolerate a missing value and still produce a prediction score. Also, a variable with a coefficient of 0 can tolerate a missing value.

If a scoring coefficient in the SCORE= data set has a missing value for an observation, the coefficient is not used in creating the new score variable for the observation. In other words, missing values of scoring coefficients are treated as zeros. This treatment affects only the observation in which the missing value occurs.