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New infrastructure for harmonized longitudinal data with MIDUS and DDI

Presenter 1
Jeremy Iverson
Presenter 2
Barry Radler
University of Wisconsin
Presenter 3
Dan Smith

Researchers wishing to use data from longitudinal studies or to replicate other’s research must currently navigate thousands of variables across multiple waves and datasets to answer simple analysis questions. A tool that allows researchers to create documented and citable data extracts that are directly related to their queries would allow more time to be spent on public health research questions instead of data management. MIDUS (Midlife in the United States) is a national longitudinal study of approximately 10,000 Americans designed to study aging as an integrated biopsychosocial process. The study has a unique blend of social, health, and biomarker data collected over several decades. In late 2013, the the United States National Institutes of Health funded MIDUS to create a DDI-based, harmonized data extraction system. This tool 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. This session will discuss project background and demonstrate the current state of the software.

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