James Wagner, Ph.D. is a Research Professor at the University of Michigan’s Survey Research Center (UM-SRC). His research is in the area of survey nonresponse and methods for addressing it during data collection. He has co-authored a book on adaptive survey design — which is a set of methods that aims to optimize the recruitment of heterogeneous samples to participate in surveys. He has a strong focus on measures of data quality, particularly related to missing data.
He is currently UM-PI for the Army study to Assess Risk & Resilience in Servicemembers — Longitudinal Study. This is a panel study of mental health among soldiers and veterans. The study involves the linkage of survey and administrative data in order to predict mental health outcomes.
He is also a co-developer for a Coursera course on data quality. The course covers methods for identifying, measuring, and correcting error in data gathered from surveys, administrative data, and other sources.
He has had a focus on multiple aspects of data quality — a “total data quality” perspective. He believes that this perspective can be helpful as a conceptual framework for those working across data from multiple sources.