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Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps (2017)

Chapter: Appendix B: Biographical Sketches of Panel Members and Staff

« Previous: Appendix A: Executive Summary from "Innovations in Federal Statistics: Combining Data Sources While Protecting Privacy"
Suggested Citation:"Appendix B: Biographical Sketches of Panel Members and Staff." National Academies of Sciences, Engineering, and Medicine. 2017. Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps. Washington, DC: The National Academies Press. doi: 10.17226/24893.
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Appendix B

Biographical Sketches of Panel Members and Staff

Robert M. Groves (Chair) is the provost, Gerard Campbell professor in the Department of Mathematics and Statistics, and a professor in the Department of Sociology, all at Georgetown University. His research focuses on the effects of the mode of data collection on responses in sample surveys, the social and political influences on survey participation, the use of adaptive research designs to improve the cost and error properties of statistics, and how public concerns about privacy affect attitudes toward statistical agencies. Previously, he served as director of the U.S. Census Bureau, director of the University of Michigan Survey Research Center, and research professor at the Joint Program in Survey Methodology at the University of Maryland. He is an elected member of the National Academy of Sciences, the National Academy of Medicine, the American Academy of Arts and Sciences, and the International Statistical Institute and an elected fellow of the American Statistical Association. His 1989 book, Survey Errors and Survey Costs, was named one of the 50 most influential books in survey research by the American Association of Public Opinion Research. He has a bachelor’s degree from Dartmouth College, master’s degrees in statistics and sociology from the University of Michigan, and a doctorate in sociology from the University of Michigan.

Michael E. Chernew is a professor of health care policy in the Department of Health Care Policy at Harvard Medical School. He is also a research associate of the National Bureau of Economic Research. His research examines areas related to controlling health care spending growth while maintaining or improving the quality of care, including consumer incentives to

Suggested Citation:"Appendix B: Biographical Sketches of Panel Members and Staff." National Academies of Sciences, Engineering, and Medicine. 2017. Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps. Washington, DC: The National Academies Press. doi: 10.17226/24893.
×

align patient cost sharing with clinical value. Related research examines the effects of changes in Medicare Advantage payment rates, as well as the causes and consequences of rising health care spending and geographic variation in spending, spending growth, and quality. He is a member of the Medicare Payment Advisory Commission, an independent agency that advises Congress. He is a recipient of the John D. Thompson Prize for Young Investigators given by the Association of University Programs in Public Health and of the Alice S. Hersh Young Investigator Award from the Association of Health Services Research. He has a B.A. from the University of Pennsylvania and a Ph.D. in economics from Stanford University.

Piet Daas is a senior methodologist in the Department of Corporate Services, Information Technology, and Methodology and a data scientist in the Center for Big Data Statistics of Statistics Netherlands. His work focuses on the use of secondary (nonsurvey) data for official statistical purposes, which began with the use of administrative data, and more recently has focused on studies in which Internet and other big data sources are used for official statistics. At Statistics Netherlands, he is a member of the big data core team, which oversees all big data activities of production, information technology, research, management, and training. He teaches the big data component of the European Master of Official Statistics track at the University of Utrecht, is involved in the big data courses of the European Statistical Training Programme, and is a member of the team organizing DataCamps (‘hackatons’) at the University of Twente. He is active in various European, U.N., and U.N. Economic Commission for Europe big data initiatives. He has an M.S. and a Ph.D. in the natural sciences with honors from the University of Nijmegen in The Netherlands.

Cynthia Dwork, on leave from Microsoft Research, is the Gordon McKay professor of computer science at the John A. Paulson School of Engineering and Applied Sciences and a Radcliffe alumnae professor at the Radcliffe Institute for Advanced Study, both at Harvard University. Her work focuses on placing privacy-preserving data analysis on a mathematically rigorous foundation: a cornerstone of this work is differential privacy, a strong privacy guarantee frequently permitting highly accurate data analysis. She also does work in cryptography and distributed computing, including work on the first public-key cryptosystem for which breaking a random instance is as hard as solving the hardest instance of the underlying mathematical problem on combating e-mail spam by requiring a proof of computational effort (the technology that underlie hashcash and bitcoin). She is a recipient of the PET Award for Outstanding Research in Privacy Enhancing Technologies given by Microsoft and of the Edsger W. Dijkstra Prize, awarded jointly by the ACM Symposium on Principles of Distributed Computing of

Suggested Citation:"Appendix B: Biographical Sketches of Panel Members and Staff." National Academies of Sciences, Engineering, and Medicine. 2017. Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps. Washington, DC: The National Academies Press. doi: 10.17226/24893.
×

the Association for Computing Machinery and the European Association for Theoretical Computer Science Symposium on Distributed Computing. She is a member of the National Academy of Sciences and the National Academy of Engineering and a fellow of the American Academy of Arts and Sciences. She has a B.S.E. from Princeton University and a Ph.D. in computer science from Cornell University.

Ophir Frieder is the Robert L. McDevitt, K.S.G., K.C.H.S. and Catherine H. McDevitt, L.C.H.S., chair in computer science and information processing at Georgetown University. He is also professor of biostatistics, bioinformatics, and biomathematics in the Georgetown University Medical Center and the chief scientific officer for UMBRA Health Corporation. He previously served as chair of the Department of Computer Science at Georgetown University. His research interests focus on scalable information retrieval systems spanning search and retrieval and communications issues in multiple domains, systems that are deployed worldwide in commercial and governmental production environments. He is a fellow of the American Association for the Advancement of Science, the Association for Computing Machinery, the Institute of Electrical and Electronics Engineers, and the National Academy of Inventors.

Brian Harris-Kojetin (Study Director) is the director of the Committee on National Statistics (CNSTAT) and served as the study director for this project. Previously, he served as deputy director of CNSTAT. Prior to that, he worked at the U.S. Office of Management and Budget (OMB), where he served as senior statistician in the Statistical and Science Policy Office. He chaired the Federal Committee on Statistical Methodology and was the lead at OMB on issues related to standards for statistical surveys, survey nonresponse, measurement of race and ethnicity, and confidentiality of statistical data. He also previously was senior project leader of research standards and practices at the Arbitron Company and a research psychologist in the Office of Survey Methods Research in the Bureau of Labor Statistics. He is a fellow of the American Statistical Association. He has a B.A. in psychology and religious studies from the University of Denver and a Ph.D. in social psychology from the University of Minnesota.

H.V. Jagadish is the Bernard A. Galler collegiate professor of electrical engineering and computer science and distinguished scientist at the Institute for Data Science at the University of Michigan in Ann Arbor. Previously, he was head of the Database Research Department at AT&T Labs in Florham Park, New Jersey. He works widely in information management and holds numerous patents in the field. He is a fellow of the Association for Computing Machinery (ACM), serves on the board of the Computing

Suggested Citation:"Appendix B: Biographical Sketches of Panel Members and Staff." National Academies of Sciences, Engineering, and Medicine. 2017. Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps. Washington, DC: The National Academies Press. doi: 10.17226/24893.
×

Research Association, and was a trustee of the VLDB [very large database] Foundation. He is a recipient of the SIGMOD Contributions Award from the ACM and of the David E. Liddle Research Excellence Award from the University of Michigan. He has a B.Tech. from the Indian Institute of Technology, Delhi, and an M.S. and a Ph.D. from Stanford University, all in electrical engineering.

Frauke Kreuter is a professor in the Joint Program in Survey Methodology at the University of Maryland and professor of statistics and methodology at the University of Mannheim, Germany. She is also affiliated with the Maryland Population Research Center, the Institute for Social Research in Michigan, and the German Institute for Employment Research. Previously, she held positions at the Institute for Statistics at the Ludwig-Maximilians University in Munich, Germany, and in the Department of Statistics at the University of California, Los Angeles. Her research focuses on nonresponse errors, paradata and responsive designs, record linkage, and, recently, issues of linkage consent and generalizability for nonprobability samples. She is an elected fellow of the American Statistical Association, and she is a recipient of the Gertrude Cox Award from the Washington Statistical Society. She serves on the advisory boards of Statistics Canada, Statistics Sweden, the U.S Bureau of Labor Statistics, the U.S. Energy Information Association, and the ad hoc committee for the Germany 2021 census. She has a B.A. and an M.A. in sociology and a Ph.D, all from the University of Konstanz in Germany.

Sharon Lohr is a vice president and senior statistician at Westat in Rockville, Maryland. Previously, she was dean’s distinguished professor of statistics at Arizona State University. Her research has focused on survey sampling, hierarchical models, small-area estimation, missing data, and design of experiments. She is a fellow of the American Statistical Association, and an elected member of the International Statistical Institute. She was the inaugural recipient of the Washington Statistical Society’s Gertrude M. Cox Statistics Award for contributions to the practice of statistics and a recipient of the society’s Morris Hansen Lecture Award. She was recently selected to present the Deming Lecture at the Joint Statistical Meetings. She has a Ph.D. in statistics from the University of Wisconsin–Madison.

James P. Lynch is a professor and chair of the Department of Criminology and Criminal Justice at the University of Maryland. Previously, he served as the director of the Bureau of Justice Statistics at the U.S. Department of Justice and was a distinguished professor in the Department of Criminal Justice at John Jay College of the City University of New York. He also previously was a professor and chair of the Department of Justice, Law and Society at

Suggested Citation:"Appendix B: Biographical Sketches of Panel Members and Staff." National Academies of Sciences, Engineering, and Medicine. 2017. Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps. Washington, DC: The National Academies Press. doi: 10.17226/24893.
×

American University. His research focuses on victim surveys, victimization risk, the role of coercion in social control, and crime statistics. He has been vice president of the American Society of Criminology and served on the Committee on Law and Justice Statistics of the American Statistical Association. He has a B.A. from Wesleyan University and an M.A. and a Ph.D. in sociology from the University of Chicago.

Colm A. O’Muircheartaigh is a professor and former dean of the Harris School of Public Policy Studies and a senior fellow at NORC, both at the University of Chicago. Previously, he was the first director of the Methodology Institute and a faculty member of the Department of Statistics at the London School of Economics and Political Science. The primary focus of his work is on the design of complex surveys across a wide range of populations and topics and on fundamental issues of data quality, including the impact of errors in responses to survey questions, cognitive aspects of question wording, and latent variable models for nonresponse. He is a fellow of the Royal Statistical Society and of the American Statistical Association and an elected member of the International Statistical Institute. He has served as a consultant to a wide range of public and commercial organizations around the world, including the OECD and the United Nations. He received his undergraduate education at University College Dublin and his graduate education at the London School of Economics.

Trivellore Raghunathan is the director of the Survey Research Center and a research professor at the Institute for Social Research at the University of Michigan, where he is also a professor of biostatistics and an associate director of the Center for Research on Ethnicity, Culture and Health in the School of Public Health. He is also a research professor in the Joint Program in Survey Methodology at the University of Maryland. Previously, he was on the faculty in the Department of Biostatistics at the University of Washington. His research interests are in the analysis of incomplete data, multiple imputation, Bayesian methods, design and analysis of sample surveys, combining information from multiple data sources, small-area estimation, confidentiality and disclosure limitation, longitudinal data analysis, and statistical methods for epidemiology. He has developed SAS-based software for imputing the missing values for a complex dataset. He has a Ph.D. in statistics from Harvard University.

Roberto Rigobon is the Society of Sloan Fellows professor of management and professor of applied economics at the Sloan School of Management at the Massachusetts Institute of Technology (MIT). He is also a visiting professor at the Instituto de Estudios Superiores de Administración (Institute of Advanced Studies in Administration) in Venezuela and a research associate

Suggested Citation:"Appendix B: Biographical Sketches of Panel Members and Staff." National Academies of Sciences, Engineering, and Medicine. 2017. Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps. Washington, DC: The National Academies Press. doi: 10.17226/24893.
×

of the National Bureau of Economic Research. His research has addressed the causes of balance-of-payments crises, financial crises, and the propagation of them across countries. He is currently studying the properties of international pricing practices and how to produce alternative measures of inflation. He is one of the two founding members of the Billion Prices Project, as well as a cofounder of PriceStats. He is a member of the Census Bureau’s Scientific Advisory Committee and the current president of the Latin American and Caribbean Economic Association. He has a B.S. in electrical engineering from Universidad Simon Bolivar (Venezuela), an M.B.A. from Instituto de Estudios Superiores de Administración (Venezuela), and a Ph.D. in economics from MIT.

Marc Rotenberg is a president of the Electronic Privacy Information Center (EPIC) in Washington, D.C., and teaches information privacy law and open government at Georgetown University Law Center. He has testified before Congress on more than 60 occasions and authored more than 50 amicus briefs on emerging privacy and civil liberties issues. He has served on several national and international advisory panels, including the expert panels on Cryptography Policy and Computer Security for the OECD and the Legal Experts on Cyberspace Law for UNESCO. He is founding board member and former chair of the Public Interest Registry, which manages the .ORG domain. He is a fellow of the American Bar Foundation, a member of the Council on Foreign Relations, and the recipient of several awards, including the World Technology Award in Law from the World Technology Network. He has an A.B. from Harvard College, a J.D. from Stanford Law School, and an LL.M. in international and comparative law from Georgetown University.

Suggested Citation:"Appendix B: Biographical Sketches of Panel Members and Staff." National Academies of Sciences, Engineering, and Medicine. 2017. Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps. Washington, DC: The National Academies Press. doi: 10.17226/24893.
×
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Suggested Citation:"Appendix B: Biographical Sketches of Panel Members and Staff." National Academies of Sciences, Engineering, and Medicine. 2017. Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps. Washington, DC: The National Academies Press. doi: 10.17226/24893.
×
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Suggested Citation:"Appendix B: Biographical Sketches of Panel Members and Staff." National Academies of Sciences, Engineering, and Medicine. 2017. Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps. Washington, DC: The National Academies Press. doi: 10.17226/24893.
×
Page 177
Suggested Citation:"Appendix B: Biographical Sketches of Panel Members and Staff." National Academies of Sciences, Engineering, and Medicine. 2017. Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps. Washington, DC: The National Academies Press. doi: 10.17226/24893.
×
Page 178
Suggested Citation:"Appendix B: Biographical Sketches of Panel Members and Staff." National Academies of Sciences, Engineering, and Medicine. 2017. Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps. Washington, DC: The National Academies Press. doi: 10.17226/24893.
×
Page 179
Suggested Citation:"Appendix B: Biographical Sketches of Panel Members and Staff." National Academies of Sciences, Engineering, and Medicine. 2017. Federal Statistics, Multiple Data Sources, and Privacy Protection: Next Steps. Washington, DC: The National Academies Press. doi: 10.17226/24893.
×
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The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics.

The panel's first report described federal statistical agencies’ current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy.

This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.

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