CORE--BIOSTATISTICS AND DATA MANAGEMENT CORE

$0P30FY2002AGNIH

Wake Forest University Health Sciences, Winston-Salem NC

Investigators

Linked publications & trials

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Abstract

DESCRIPTION (provided by applicant): We propose a Biostatistics and Data management Core (RC-C) for WFUSM's Older Americans Independence Center (OAIC). The aims of this Core are to provide personnel and other resources to: 1. Provide data management support, sample size determinations and statistical analyses related to the addition of muscle strength, physical performance, genetics, body composition and disability variables to ongoing independently funded projects (REACT II; RESTORE; PIE; EFIT; Growth hormones and age-related pathogenesis; Role of ion channels in sarcopenia). For this aim, close collaboration will be needed with the Body Composition, Clinical Research, Pre-clinical Research and Genomics and Biomarkers Cores. 2. Provide data management, design, and statistical analysis for research development projects aimed at investigating (a) In vitro mechanisms of skeletal muscle function (Leader -- Nicklas), (b) muscle composition and function through magnetic resonance spectroscopy (Leader-- Baumgartner), and (c) extending a translational model of disability to include mice (Leader -- Carter). 3. Provide data management, design, and statistical analysis for pilot and exploratory projects. 4. Provide data management support to create analysis databases and provide statistical support for reanalysis of existing OAIC databases (e.g., FAST, ADAPT, ACE, OASIS) to address scientific questions related to the role of muscle loss and sarcopenia as determinants of the decline in physical function and progression to physical disability in older persons. 5. Assist the Recruitment Core with monitoring recruitment, adherence and retention. 6. Develop biostatistical research directly related to analytical issues (this aim will be addressed in years 2-5 of OAIC funding) The Biostatistics Core will provide assistance with methodological, statistical, quality control and computational issues, including study design, data collection, computer networking, database management, data analysis, and presentation of results for publication.

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