Data Management and Statistical Core

$214,337P50FY2015AGNIH

University Of Southern California, Los Angeles CA

Investigators

Linked publications & trials

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Abstract

ABSTRACT: DATA MANAGEMENT AND BIOSTATISTICAL CORE The overall objective of the Data Management and Statistical Core is to provide high quality services and resources to Clinical, Neuropathology, Imaging and Education Cores, and ADRC investigators (including ADRC projects, pilots, and ADRC-affiliated investigators). Over the past funding period, the Data Core has continued to contribute significantly to the ongoing data management related to subject recruitment, tracking and data collection and sharing. We have further made major biostatistical contributions to dementia-related research at USC, contributing to clinical trials designs and analyses related to metabolic and vascular contributions to cognition/dementia. In this renewal period, the Data Core resources will provide an informatics and statistics environment to contribute to cutting-edge dementia research both locally and nationally. Existing strengths of our Core include data management and biostatistical resources embedded within the Division of Biostatistics in the Department of Preventive Medicine, with biostatistical expertise in clinical trials and statistical genetics; Dr. Wendy Mack has extensive statistical experience in dementia-related research and clinical trials. In this competitive renewal, the Data Core has been considerably strengthened by the addition of Arthur Toga as Core Leader, bringing the unique resources of the USC Institute for Neuroimaging and Informatics (INI). The INI will support large scale data management and dissemination of imaging, genetics and other data consistent with systems supporting Alzheimer Disease Neuroimaging Initiative (ADNI), CHDI, Parkinson Progression Marker Initiative (PPMI) and others. All activities of this Core will support the mission of the ADRC as well as the broader national Alzheimer's Disease research community. The multimodality nature of data collected in the investigation of the role of vascular factors in AD requires robust informatics, data management and statistics. ¿

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