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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Methods to Foster
Transparency and
Reproducibility
of Federal Statistics

PROCEEDINGS OF A WORKSHOP

Michael L. Cohen, Rapporteur

Committee on National Statistics

Division of Behavioral and Social Sciences and Education

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THE NATIONAL ACADEMIES PRESS
Washington, DC
www.nap.edu

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
×

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This activity was supported by contracts between the National Academy of Sciences and the National Science Foundation (#SES-1024012). This grant provides support for the work of the Committee on National Statistics from a consortium of federal agencies. Any opinions, findings, conclusions, or recommendations expressed in this publication do not necessarily reflect the views of any organization or agency that provided support for the project.

International Standard Book Number-13: 978-0-309-48629-3
International Standard Book Number-10: 0-309-48629-7
Digital Object Identifier: https://doi.org/10.17226/25305

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Suggested citation: National Academies of Sciences, Engineering, and Medicine. (2019). Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: https://doi.org/10.17226/25305.

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
×

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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
×

STEERING COMMITTEE ON TRANSPARENCY AND REPRODUCIBILITY OF FEDERAL STATISTICS

WILLIAM EDDY (Chair), Department of Statistics, Carnegie Mellon University

GEORGE ALTER, Inter-university Consortium for Political and Social Research

JEREMY FREESE, Department of Sociology, Stanford University

GRAHAM KALTON, Westat

AUDRIS MOCKUS, Min H. Kao Department of Electrical Engineering & Computer Science, University of Tennessee, Knoxville

SUSAN OFFUTT, U.S. Government Accountability Office (retired)

MICHAEL L. COHEN, Study Director

MICHAEL SIRI, Program Associate

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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COMMITTEE ON NATIONAL STATISTICS

ROBERT M. GROVES (Chair), Office of the Provost, Department of Mathematics and Statistics, and Department of Sociology, Georgetown University

MARY ELLEN BOCK, Department of Statistics, Purdue University (emeritus)

ANNE C. CASE, Woodrow Wilson School of Public and International Affairs, Princeton University

MICHAEL CHERNEW, Department of Health Care Policy, Harvard Medical School

JANET M. CURRIE, Woodrow Wilson School of Public and International Affairs, Princeton University

DONALD A. DILLMAN, Social & Economic Sciences Research Center, Washington State University

DIANA FARRELL, JPMorgan Chase Institute, Washington, DC

DANIEL KIFER, Department of Computer Science and Engineering, The Pennsylvania State University

THOMAS L. MESENBOURG, U.S. Census Bureau (retired)

SARAH M. NUSSER, Office of the Vice President for Research, and Department of Statistics, Iowa State University

COLM O’MUIRCHEARTAIGH, Harris School of Public Policy, The University of Chicago

JEROME P. REITER, Department of Statistical Science, Duke University

JUDITH A. SELTZER, Department of Sociology, University of California, Los Angeles

C. MATTHEW SNIPP, Department of Sociology, Stanford University

BRIAN A. HARRIS-KOJETIN, Director

CONSTANCE F. CITRO, Senior Scholar

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
×

Acknowledgments

We would first like to thank the National Science Foundation (NSF), particularly Amy Friedlander, deputy director, Office of Advanced Cyberinfrastructure, and her colleague, Patricia Knezek, senior adviser, Mathematical and Physical Sciences Directorate (until January 2018) for their support of this project, and for Amy Friedlander’s presentation, which kicked off the workshop. In addition, John Gawalt, director (until April 2018), NSF National Center for Science and Engineering Statistics, attended the workshop and provided helpful advice on the importance of this topic for the agencies in the federal statistical system.

We are so very indebted to the presenters, who prepared extremely useful presentations and were candid about current practices at their institutions: John Abowd (U.S. Census Bureau), David Barraclough (Organisation for Economic Co-operation and Development), Wesley Basel (U.S. Census Bureau), Peter Brodie (UK Office for National Statistics), Michaela Denk (International Monetary Fund), John Eltinge (U.S. Census Bureau), Daniel Gillman (Bureau of Labor Statistics), Hermann Habermann (Committee on National Statistics), Brian Harris-Kojetin (Committee on National Statistics), Sarah Henry (UK Office for National Statistics), H.V. Jagadish (University of Michigan), Ruth Ann Killion (U.S. Census Bureau), Tom Louis (Johns Hopkins University), Jennifer Madans (National Center for Health Statistics), Peter Miller (U.S. Census Bureau), Juan Muñoz (Instituto Nacional de Estadística y Geografía), Eric Rancourt (Statistics Canada), Robert Sienkiewicz (U.S. Census Bureau), Sally Thompson (Bureau of Economic Analysis), and Lars Vilhuber (Cornell University).

Page viii Cite
Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Finally, we are also indebted to John Eltinge (U.S. Census Bureau) for helpful comments on the structure of the workshop and to Hermann Habermann, Nancy Kirkendall, and Michael Siri (Committee on National Statistics) for contributing to the planning meeting of the steering committee in October 2016 and workshop in June 2017. Furthermore, we thank Yvonne Wise, Eugenia Grohman, and Kirsten Sampson Snyder, staff members of the Division of Behavioral and Social Sciences and Education, for their efforts in editing, review, and report preparation.

This Proceedings of a Workshop was reviewed in draft form by individuals chosen for their diverse perspectives and technical expertise. The purpose of this independent review is to provide candid and critical comments that will assist the National Academies of Sciences, Engineering, and Medicine in making each published proceedings as sound as possible and to ensure that it meets the institutional standards for quality, objectivity, evidence, and responsiveness to the charge. The review comments and draft manuscript remain confidential to protect the integrity of the process.

We thank the following individuals for their review of this Proceedings: David Barraclough, Statistics and Data Directorate, Smart Data Practices and Solutions Division, Organisation for Economic Co-operation and Development, and Patrick J. Cantwell, Sampling/Estimation, U.S. Census Bureau.

Although the reviewers listed above provided many constructive comments and suggestions, they were not asked to endorse the content of this Proceedings nor did they see the final draft before its release. The review of this Proceedings was overseen by Colm O’Muircheartaigh, Harris School of Public Policy, The University of Chicago. He was responsible for making certain that an independent examination of this proceedings was carried out in accordance with standards of the National Academies and that all review comments were carefully considered. Responsibility for the final content rests entirely with the rapporteur and the National Academies.

Michael L. Cohen, Study Director

Steering Committee on Transparency and Reproducibility of Federal Statistics

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Page viii Cite
Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
×
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
×
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2019. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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In 2014 the National Science Foundation (NSF) provided support to the National Academies of Sciences, Engineering, and Medicine for a series of Forums on Open Science in response to a government-wide directive to support increased public access to the results of research funded by the federal government. However, the breadth of the work resulting from the series precluded a focus on any specific topic or discussion about how to improve public access. Thus, the main goal of the Workshop on Transparency and Reproducibility in Federal Statistics was to develop some understanding of what principles and practices are, or would be, supportive of making federal statistics more understandable and reviewable, both by agency staff and the public. This publication summarizes the presentations and discussions from the workshop.

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