DESCRIPTION (provided by applicant): It is widely acknowledged there are too few biostatisticians well-trained in the methods and content of psychiatric research. No where is this more true than in the area of pediatric treatment outcome studies. This Mentored Patient-Oriented Research Career Development Award (K23) is designed to provide the candidate, who already has substantial expertise as a pediatric clinical trialist, with advanced training in statistical and research methodology. The overall goal is to establish the candidate as an independent biostatistical investigator who can serve at the interface of research design, implementation, and statistical methods in pediatric interventions research and contribute to the development of new knowledge and new statistical and research methods. Exemplary mentors, with complementary skills, will advise and supervise the candidate's didactic agenda, which includes formal coursework in advanced biostatistics, directed readings, tutorials, and participation in seminars and conferences. Primary sponsor, Dr. Susan Silva, will advise the candidate's training in the area of research design, statistics, and clinical trails management. Co-sponsor, Dr. John March, will provide oversight as the candidate transitions from clinical trialist to an independent investigator with expertise in research design and advanced statistical methods, and will collaborate with the candidate on multiple NIMH- funded trials for which he is the Principal Investigator. Co-sponsors Drs. Satish lyengar, James Rochon, Marie Davidian, and Thomas Ten Have will supervise the candidate's training in advanced data analytic methods related to their area of expertise. The candidate will use available data sets from two NIMH-funded pediatric comparative treatment trials to address research questions that are of direct relevance to clinicians and individuals making decisions regarding patient care. The primary aim of the candidate's research agenda is to apply and extend data analytic methods appropriate for drawing causal inference from complex multisite pediatric comparative treatment trials [e.g., compiler average causal effect (CAGE) and structural mean model (SMM)j. The research plan also focuses broadly on applying advanced quantitative methods for analyzing clinical trials data. These analyses will help the field better understand the essential treatment elements and mechanisms associated with successful evidence-based treatments for pediatric anxiety disorders. The complementary career development and research plans will help position the candidate as an independent biostatistical investigator who will be able to make original and unique contributions in the areas of applied quantitative and clinical trials methodologies and serve as a statistical and methodological consultant to multidisciplinary research teams and make original and unique contributions to the scientific field of applied quantitative methodology and clinical trials methodologies.