The goal of this project is to develop a method for creating algorithmically generated control groups – virtual controls – for use in evaluating alcohol and drug prevention studies. These control cases will have two characteristics: (1) pretest similarity to whatever prevention treatment group may present itself and (2) patterns of change over time that closely mimic the normal course of alcohol and drug use development. Specifically, this method will provide a means to evaluate the effectiveness of alcohol and drug prevention programs that are disseminated when randomization cannot occur. This method will also make evaluating new and adapted programs easier by reducing the challenges of recruitment, subject retention, and onsite data collection and pretest non-equivalence that often occur when classrooms, schools and communities are assigned to condition.