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Federal Statistics, Multiple Data Sources, and Privacy Protection Next Steps (2017) / Chapter Skim
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Summary
Pages 1-4

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From page 1...
... 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 (see Executive Summary in Appendix A)
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From page 2...
... Methods for Combining Data  Statistical methods that are currently available, such as record linkage techniques, dual frame estimation, imputationbased models, and small-area estimation methods can be used to combine data sources and develop statistical estimates for characteristics of interest. The panel recommends that federal statistical agencies redesign current data collection efforts and estimation using multiple data sources, adapt current statistical methods to combine data sources, and develop partnerships with academia and external research organizations to develop the new methods needed for design and analysis using multiple data sources.
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From page 3...
... The entity should follow the principles and practices for federal statistical agencies and permit data access only for statistical purposes. The panel's proposed new entity should assist federal statistical agencies in identifying data sources that can most effectively inform the creation of national statistics, help develop techniques to use those data to compute national statistics while respecting privacy and other protection obligations on the data, and nurture the expertise required for these activities.
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From page 4...
... These areas include statistical methods for combining multiple data sources; various aspects of data quality and the appropriate metrics and methods for examining data quality from different sources; and modern computer science technology, including but not limited to distributed computing, database management, cryptography, and privacy-preserving and privacy-enhancing technologies.
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