In reply to Samir.

Thanks for writing. The ROBUSTREG procedure does two things: (1) it finds high-leverage points among the explanatory variables (the X variables), and (2) it finds outliers among the response values and solves a robust regression problem. This article is about (1) and those estimates depend only on the explanatory variables, so the response doesn't matter for forming those estimates. (Other ROBUSTREG output might change.) However, the estimation process itself (for LTS and M-estimation) uses random subsets of the data, so the estimates could change because of the subsets that are examined. You can add a seed value (for example, SEED=54321) to the PROC ROBUSTREG statement to ensure that the subsets are the same every time that you run the procedure.