Prevention and developmental sciences have many complementary goals and much to gain by collaboration. With random assignment to conditions and long-term multivariate follow-up of individuals across significant years in the life span, fundamental basic and applied research questions can now be addressed using new statistical methods. This special issue includes four empirical papers that used growth modeling techniques (hierarchical linear modeling, latent growth curve analyses) to examine direct and indirect effects of theory-based, longitudinal prevention experiments on developmental trajectories of children''s and adolescents'' substance use, delinquency, and school bonding.

Prevention and developmental sciences have many complementary goals and much to gain by collaboration. With random assignment to conditions and long-term multivariate follow-up of individuals across significant years in the life span, fundamental basic and applied research questions can now be addressed using new statistical methods. This special issue includes four empirical papers that used growth modeling techniques (hierarchical linear modeling, latent growth curve analyses) to examine direct and indirect effects of theory-based, longitudinal prevention experiments on developmental trajectories of children''s and adolescents'' substance use, delinquency, and school bonding.