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Building a DDI-based (3.2) Harmonized Data Extract Tool for MIDUS: An Update

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Author: Smith, Dan
Many longitudinal studies of health and aging contain thousands of variables and pose particular challenges for researchers who wish to analyze the data themselves or replicate others’ research. MIDUS (Midlife in the United States) is a national longitudinal study of approximately 10,000 Americans designed to study aging as an integrated bio-psychosocial process. The study has a broad and unique blend of social, health, and biomarker data collected over several decades through a variety of modes. Recently the study has added new longitudinal cohorts that make data management, interpretation, and analysis even more challenging. A tool that allows researchers to easily create documented and citable data extracts that are directly related to their research questions would allow more time to be spent on public health research questions instead of data management. In late 2013, the United States National Institutes of Health funded MIDUS to create a DDI-based, harmonized data extraction system. This presentation is an update on progress towards creation of a DDI-based tool that will facilitate identification and harmonization of similar MIDUS variables, while enhancing the MIDUS online repository with a data extract function. This will accomplish something unprecedented: the ability to obtain customized cross-project downloads of harmonized MIDUS data that are DDI-compliant. Doing so will greatly enhance efficient and effective public use of the large longitudinal and multi-disciplinary datasets that comprise the MIDUS study.
Barry Radler (University of Wisconsin, Institute on Aging), Jeremy Iverson and Dan Smith (Colectica)
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