Don has over 25 years of experience managing and directing large-scale national federal statistical projects and methodological research associated with federal statistics programs. Don leads a group of statisticians and data scientists with expertise in design and analytic techniques necessary for social science research. He helped his team establish roles in complex sample designs, experimental and observational study designs, data collection and processing, and statistical inference. In the wake of big data and data analytics, he led his group to augment their roles by expanding modern capabilities in data analytics, advanced statistical computing, Bayesian modeling, data mining, and machine learning. As research embraces more timely and cost-efficient data to include newer research methodologies, such as data analytics and rapid-cycle evaluation, so have the services and resources offered by the Data Science group he leads. His vision to bring data scientific and statistical values to evidence-based social science research and informed decision-making has continued to be realized under his leadership. Through seamless integration with NORC’s research team, our Data Science group can implement high-level, high-quality methodologies, providing a strong statistical framework for every research project.
Don’s longtime commitment to supporting the National Science Foundation’s NCSES programs dates back to his tenure at Mathematica. Don has led all statistical tasks for the Scientists and Engineers Statistical Data System (SESTAT) project since 1996. The SESTAT database integrates data collected through three national sample surveys supported by the National Science Foundation (NSF): the National Survey of College Graduates (NSCG), the Survey of Doctorate Recipients (SDR), and the National Survey of Recent College Graduates (NSRCG). For that project, Don has led all activities needed for statistical support of the SESTAT system, including linking multiple survey data; optimum sample allocation to meet several statistical precision goals; dynamic, streamlined, real-time data processing for data editing, imputation, and model-based weighting production for large scale data collection, developing SESTAT variance estimation methodologies, constructing longitudinal weights for longitudinal data analysis, and providing general statistical consultations to NSF and data collection contractors.
Don led the Agency for Healthcare Research and Quality (AHRQ)’s data innovation projects to help create new data products that fill crucial data gaps and inform health care policy and research to address the nation’s emerging health issues. Data products include Synthetic Healthcare Database for Research (SyH-DR), Social Determinants of Health Research Database (SDOH-RD), and Physician and Physician Research Database (3P-RD).
Don is an elected fellow of the American Statistical Association (ASA). He served on the ASA board of directors from 2018 to 2020. He served as Chair-elect for the Survey Research Method Section of ASA for the 2024 term to eventually serve as Chair. He also served as President of the Korean International Statistical Society from 2019 to 2020. He was a board member of Hope Nicaragua from 2007 to 2018.
Press Release | August 29, 2022
Journal Article | February 16, 2022
American Statistical Association Honors Five Members of NORC Senior Staff for Their Industry Contributions
Press Release | July 27, 2018
Don Jang, Vice President of NORC and Director of its Center for Excellence in Survey Research, Elected President of the Korean International Statistical Society
Press Release | February 13, 2017
Donsig Jang Named Vice President and Director of the Center for Excellence in Survey Research at NORC at the University of Chicago
Press Release | October 1, 2016
"Adjustments for Misclassification of Deployment Status in a Population-Based Health Study of Operation Enduring Freedom and Operation Iraqi Freedom Veterans."
Journal Article | November 13, 2013
opens in new tab"Implementing Multiple Evaluation Techniques in Statistical Disclosure Control for Tabular Data."
Journal Article | December 6, 2012
Journal Article | November 13, 2011