The Data Management and Biostatistics Core (Data Core) performs data management and analysis for all six fellow cores (Administrative, Clinical, Neuropathology, Neuroimaging, Psychosocial, Education), and for individual researchers affiliated with the ADCC. The Data Core maintains all data collected by the NYU ADCC in a centralized database, transfers data to the National Alzheimer's Coordinating Center (NACC) to create a common database for all ADCC's and ADRC's, and offers consultation and hands-on help in experimental design and statistical analysis to all collaborating investigators in the ADCC. The rapid increase in the size, the type and the complexity of aging and dementia related data demands that the Data Core expand its functions in order to (1) facilitate information exchange via the Internet, and (2) introduce, apply and develop novel statistical methods for comprehensive data analysis. The Data Core Specific Aims are: 1. Continue to provide its traditional data management and statistical consultation services which include managing and updating the centralized Center database, offering consultation on experimental design and statistical analysis, and maintaining close collaboration with the NACC in the implementation of the uniform data set for all ADC's. 2. Further develop and maintain a secure Web-based database for multi-user on-line information exchange within the Center and between centers/NACC/other collaborators. In particular, we will upgrade our Visual FoxPro database server to a more web-friendly and versatile Microsoft SQL server. 3. Actively initiate, develop, participate in and direct statistical analyses within and between our fellow cores/centers. Data Core analysts (including student trainees) are assigned to fellow cores to increase interactions and understanding, and foster close collaborations in design and analysis. Data Core leader conducts biweekly meetings with Core analysts and communicates with NACC for collaborative analysis. 4. Educate Center affiliated researchers on database utilization and related statistical analysis methods. This will be achieved through a comprehensive intranet site with detailed education topics and on-line help.
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