This research focuses on the development of new data analytic methods for developing adaptive interventions, which hold the promise of improving long-term outcomes for greater numbers of persons with substance use disorder. Adaptive interventions are designed to deliver an appropriate intervention to those who need it, when they need it, thereby maximizing the effect of the intervention. The sequential multiple assignment randomized trial (SMART), a major step forward in the science of adaptive interventions, is an experimental design explicitly for identifying and constructing efficacious adaptive interventions. However, in order to make the SMART maximally useful to drug use and HIV intervention scientists, methodological work is needed to expand the options for analyzing data that arise from a SMART. This project focuses on the development of new multilevel methods for analyzing longitudinal outcome measures arising from a SMART in the area of drug-use and HIV; developing new sample size calculators for planning SMART studies with longitudinal outcome measures; and applying these methods using data from three completed SMART studies. The methods developed in this project will improve clinical and public health outcomes by enabling drug use and HIV scientists to develop more potent adaptive interventions to guide the individualization of drug use and HIV treatments.