Creating a harmonized custom data extract for MIDUS using DDI 3.2

A DDI-based extraction tool for harmonized longitudinal data.

Adhering to a metadata standard greatly clarifies the processes used to capture and produce datasets, and provides users of those datasets the information needed to analyze, interpret, and preserve them. Standards are even more important with longitudinal studies that contain thousands of variables and many different data types.

The MIDUS study (Midlife in the United States) is a complex longitudinal study of health and well-being with widespread secondary usage, largely due to its availability through NACDA and ICPSR. Conceiving of aging as an integrated bio-psychosocial process, MIDUS has a broad and unique blend of social, health, and biomarker data collected over 20 years through a variety of modes. For nearly 10 years, MIDUS has relied on DDI to help manage and document these complex research data. In late 2013, the National Institute on Aging funded MIDUS to upgrade its DDI infrastructure to version 3.2 and create a DDI-based, harmonized data extraction system. Such a system allows researchers to easily create documented and citable data extracts that are directly related to their research questions and allows more time to be spent analyzing data instead of managing it. This presentation will explain the rationale, methods, and results of the project.

Presented by Barry T. Radler, Ph.D.
University of Wisconsin-Madison
Researcher, Institute on Aging
Monday, May 4, 2015