BIOSTATISTICS AND DATA MANAGEMENT CORE

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We propose continuation of the Biostatistics and Data Management Core (RC3) for the WFU Older Americans Independence Center (OAIC). The aims of this Core are to provide collaborative support and other resources related to: 1. Study design, sample size determination, data management and statistical analysis for projects (pilot and developmental) investigating the multiple factors that contribute to age-related increases in adiposity, sarcopenia, declines in muscle function, physical function decline and progression to disability. 2. Data management and statistical analyses of muscle strength, physical performance, body composition, fat distribution, and genetic, biological, and disability measures that are added to 9 ongoing externallyfunded projects, 3 pilots, and 2 Research Development projects (initial year). The ongoing close collaborations with the Biolmaging, Clinical Research, Molecular Sciences Resource, and Pilot and Exploratory Studies Cores are an important aspect of this aim. 3. Training of RCDC-supported fellows on the design, planning, conduct and analysis of results of agingrelated research projects. 4. Data management and statistical analyses of existing databases (e.g., REACT II, PIE, TRAIN, Health ABC, MESA, etc.) to allow for re-analyses to address scientific questions on the roles of obesity and muscle loss as determinants of the decline in physical function and progression to physical disability in older persons. 5. Data management and report generation to assist the Clinical Research Core with monitoring recruitment, adherence and retention, and the Molecular Sciences Resource Core with monitoring and promoting of a biological specimen repository. 6. Development of novel biostatistical methods and techniques directly related to analytical issues associated with aging research. 7. Web-based tools useful for the Leadership and Administrative Core to streamline communication and document management within WFU's OAIC. The Biostatistics and Data Management Core will actively collaborate on methodological, statistical, quality control and computational issues, including study design, data collection, computer networking, database management, data analysis, and presentation of results for publication