In reply to Michael O'Neil.

It sounds like you are identifying influential observations. You then eliminate them to obtain a model that has better predictive properties. This ad-hoc process is similar to fitting a robust regression model. Since robust regression has 50+ years of research behind it, I would encourage you to use those techniques. An early SAS paper on robust regression is Chen 2002, which discusses the ROBUSTREG procedure, but there has been a lot of additional progress since then. For generalized linear models, such as logistic regression, some SAS programmers use PROC NLMIXED.