The NSF-Census Research Network has been awarded the American Statistical Association’s Statistical Partnerships Among Academe, Industry, and Government (SPAIG) Award

Baltimore, MD The National Science Foundation-Census Research Network (NCRN) has been awarded the American Statistical Association’s Statistical Partnerships Among Academe, Industry, and Government (SPAIG) Award. The award recognizes excellence in collaboration between academe, industry, and government that results in significant contributions to statistics with applications to real-world problems. The award was announced at the ASA’s Joint Statistical Meetings in Baltimore, MD on July 30, 2017.

A greatly abbreviated listing of benefits includes:

  • New method for simultaneous editing and imputation. Method has applications for improving the accuracy of the tabulations from the Economic Census.
  • Production of synthetic business microdatasets allowing the agency to meet data user needs while protecting data confidentiality.
  • Quality models of the 2020 Census, predicting coverage errors at the national level under different spending constraints.
  • Privacy and confidentiality studies related to use of maps and geolocation necessary to enumerate 2020 Census web respondents without an ID.
  • Development of a new data documentation system under consideration to ease external access to internal data.

Other activities that encouraged partnership included monthly virtual seminars, NCRN conferences, workshops, and college courses. A twice-yearly NCRN conference features the work of the grantees. Conferences are free and open to the public with the goal of making the NCRN research known to the wider federal statistical community. The NCRN also sponsored several workshops covering topics such as analysis of spatio-temporal modeling, analysis of SIPP data, and geo-spatial statistics. Additional key outputs and successes of the partnership include support and engagement of over 90 students pursuing research projects and dissertations directly relevant to the statistical agencies, development of full length courses/short courses including courses on problems statistical agencies face; social and economic data; spatio-temporal statistical modeling (see current list at, publicly available software and datasets including “Naturally Occurring Data” public-use datafile; multiple imputation R package, and more (full list at, applied work products related to spatial-temporal modeling, geo-spatial statistics, disclosure avoidance, synthetic data, Big Data applications, advances in editing and imputation, spatial visualization of uncertainty and user-defined geographies to reduce margin of error; and “smart-agent” internet data collection designs. A full biography of publications and working papers can be found at

The NCRN tackled “challenging issues that could not have been addressed so productively by either academic or government researchrs acting on their own”, said Prof. Sarah Nusser, Vice-President for Research at Iowa State University, and Dr. Nancy Potok, Chief Statistician of the United States, noted that based on her own observation, “the collaboration has been highly successful”.

The NCRN is composed of nodes at eight universities (Carnegie Mellon University, University of Colorado joint with the University of Tennessee, Cornell University, Duke University joint with the National Institute of Statistical Science, University of Michigan, University of Missouri, University of Nebraska, and Northwestern University) and the United States Census Bureau, and was  established in 2011 to provide support for a set of research nodes, staffed by teams of researchers conducting interdisciplinary research and educational activities on methodological questions of interest and significance to the broader research community and to the federal statistical system, particularly the U.S. Census Bureau. The Coordinating Office for the NCRN, created in 2012 and managed by Cornell University and Duke/NISS, organized conferences and workshops, compiled the NCRN newsletter, and served as the primary marketing mechanism for NCRN public forums and work products.

More information on the NCRN and its nodes can be found through the website at

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