This R03 project proposes to examine the feasibility of new methods for drawing causal inferences in mediation models of substance use preventive interventions. Mediation occurs when an independent variable (e.g. preventive intervention) has an effect on the dependent variable (e.g. substance use) through a third variable (e.g. resistance skills). Traditional methods for assessing mediation allow for causal inferences between the independent variable and the mediator variable but not between the mediator and the dependent variable because individuals are not randomly assigned to levels of the mediator. Although the new methods, which are based on potential outcomes, have been developed in the statistical literature, they have not been implemented in applied prevention research. Using simulation studies, the new methods will be compared with the traditional methods to determine whether they are an improvement over the traditional methods. The new methods will then be applied to a secondary data analysis of a randomized substance use prevention program for adolescents. The new methods will be implemented in software programs and macros, which will be made available free of charge to applied researchers. Methods and findings will ultimately inform the design of more cost-effective interventions for substance use prevention by allowing applied researchers to draw more valid causal inferences. PUBLIC HEALTH RELEVANCE: This project will (a) generate new statistical methods and software to enable applied researchers to draw more valid causal inferences about mediation processes, and (b) apply these methods in secondary analysis of a randomized substance use prevention intervention for adolescents. Methods and findings will ultimately inform the design of more cost-effective interventions for substance use.