B. BACKGROUND AND SIGNIFICANCE Although the research studies proposed within the Center are diverse with respect to the populations being studied, clinical contexts, and study designs, they are unified by an underlying theoretical framework, an overlapping measurement strategy, and a commitment to the collection of data of the highest quality possible. In order to fully take advantage of the common features across studies and avoid duplication of effort, centralized data management, measurement, and statistical resources are essential. The ability to carry out Center-wide analyses is another important value added feature of our approach. Both pooled analysis in which identical data from multiple studies are combined and comparative analysis can be carried out. For example, pooled analysis of the psychometric properties of instruments in the core data base will enable us to apply statistical methods that would not be possible by the limited sample size of individual studies. Similarly, only through a coordinated theoretically driven measurement and analytic approach will we be able to test hypotheses about common pathways across diverse health endpoints, including depression, obesity, and infectious disease. This approach will enable us to explore important questions regarding which pathways are uniquely linked to particular health outcomes and which pathways are common across health outcomes.