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Author: Asaph Young Chun
Publisher: John Wiley & Sons
ISBN: 1119272041
Category : Mathematics
Languages : en
Pages : 384
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Book Description
ADMINISTRATIVE RECORDS FOR SURVEY METHODOLOGY Addresses the international use of administrative records for large-scale surveys, censuses, and other statistical purposes Administrative Records for Survey Methodology is a comprehensive guide to improving the quality, cost-efficiency, and interpretability of surveys and censuses using administrative data research. Contributions from a team of internationally-recognized experts provide practical approaches for integrating administrative data in statistical surveys, and discuss the methodological issues—including concerns of privacy, confidentiality, and legality—involved in collecting and analyzing administrative records. Numerous real-world examples highlight technological and statistical innovations, helping readers gain a better understanding of both fundamental methods and advanced techniques for controlling data quality reducing total survey error. Divided into four sections, the first describes the basics of administrative records research and addresses disclosure limitation and confidentiality protection in linked data. Section two focuses on data quality and linking methodology, covering topics such as quality evaluation, measuring and controlling for non-consent bias, and cleaning and using administrative lists. The third section examines the use of administrative records in surveys and includes case studies of the Swedish register-based census and the administrative records applications used for the US 2020 Census. The book’s final section discusses combining administrative and survey data to improve income measurement, enhancing health surveys with data linkage, and other uses of administrative data in evidence-based policymaking. This state-of-the-art resource: Discusses important administrative data issues and suggests how administrative data can be integrated with more traditional surveys Describes practical uses of administrative records for evidence-driven decisions in both public and private sectors Emphasizes using interdisciplinary methodology and linking administrative records with other data sources Explores techniques to leverage administrative data to improve the survey frame, reduce nonresponse follow-up, assess coverage error, measure linkage non-consent bias, and perform small area estimation. Administrative Records for Survey Methodology is an indispensable reference and guide for statistical researchers and methodologists in academia, industry, and government, particularly census bureaus and national statistical offices, and an ideal supplemental text for undergraduate and graduate courses in data science, survey methodology, data collection, and data analysis methods.
Author: Asaph Young Chun
Publisher: John Wiley & Sons
ISBN: 1119272041
Category : Mathematics
Languages : en
Pages : 384
Get Book Here
Book Description
ADMINISTRATIVE RECORDS FOR SURVEY METHODOLOGY Addresses the international use of administrative records for large-scale surveys, censuses, and other statistical purposes Administrative Records for Survey Methodology is a comprehensive guide to improving the quality, cost-efficiency, and interpretability of surveys and censuses using administrative data research. Contributions from a team of internationally-recognized experts provide practical approaches for integrating administrative data in statistical surveys, and discuss the methodological issues—including concerns of privacy, confidentiality, and legality—involved in collecting and analyzing administrative records. Numerous real-world examples highlight technological and statistical innovations, helping readers gain a better understanding of both fundamental methods and advanced techniques for controlling data quality reducing total survey error. Divided into four sections, the first describes the basics of administrative records research and addresses disclosure limitation and confidentiality protection in linked data. Section two focuses on data quality and linking methodology, covering topics such as quality evaluation, measuring and controlling for non-consent bias, and cleaning and using administrative lists. The third section examines the use of administrative records in surveys and includes case studies of the Swedish register-based census and the administrative records applications used for the US 2020 Census. The book’s final section discusses combining administrative and survey data to improve income measurement, enhancing health surveys with data linkage, and other uses of administrative data in evidence-based policymaking. This state-of-the-art resource: Discusses important administrative data issues and suggests how administrative data can be integrated with more traditional surveys Describes practical uses of administrative records for evidence-driven decisions in both public and private sectors Emphasizes using interdisciplinary methodology and linking administrative records with other data sources Explores techniques to leverage administrative data to improve the survey frame, reduce nonresponse follow-up, assess coverage error, measure linkage non-consent bias, and perform small area estimation. Administrative Records for Survey Methodology is an indispensable reference and guide for statistical researchers and methodologists in academia, industry, and government, particularly census bureaus and national statistical offices, and an ideal supplemental text for undergraduate and graduate courses in data science, survey methodology, data collection, and data analysis methods.
Author: Asaph Young Chun
Publisher: John Wiley & Sons
ISBN: 111927205X
Category : Mathematics
Languages : en
Pages : 384
Get Book Here
Book Description
ADMINISTRATIVE RECORDS FOR SURVEY METHODOLOGY Addresses the international use of administrative records for large-scale surveys, censuses, and other statistical purposes Administrative Records for Survey Methodology is a comprehensive guide to improving the quality, cost-efficiency, and interpretability of surveys and censuses using administrative data research. Contributions from a team of internationally-recognized experts provide practical approaches for integrating administrative data in statistical surveys, and discuss the methodological issues—including concerns of privacy, confidentiality, and legality—involved in collecting and analyzing administrative records. Numerous real-world examples highlight technological and statistical innovations, helping readers gain a better understanding of both fundamental methods and advanced techniques for controlling data quality reducing total survey error. Divided into four sections, the first describes the basics of administrative records research and addresses disclosure limitation and confidentiality protection in linked data. Section two focuses on data quality and linking methodology, covering topics such as quality evaluation, measuring and controlling for non-consent bias, and cleaning and using administrative lists. The third section examines the use of administrative records in surveys and includes case studies of the Swedish register-based census and the administrative records applications used for the US 2020 Census. The book’s final section discusses combining administrative and survey data to improve income measurement, enhancing health surveys with data linkage, and other uses of administrative data in evidence-based policymaking. This state-of-the-art resource: Discusses important administrative data issues and suggests how administrative data can be integrated with more traditional surveys Describes practical uses of administrative records for evidence-driven decisions in both public and private sectors Emphasizes using interdisciplinary methodology and linking administrative records with other data sources Explores techniques to leverage administrative data to improve the survey frame, reduce nonresponse follow-up, assess coverage error, measure linkage non-consent bias, and perform small area estimation. Administrative Records for Survey Methodology is an indispensable reference and guide for statistical researchers and methodologists in academia, industry, and government, particularly census bureaus and national statistical offices, and an ideal supplemental text for undergraduate and graduate courses in data science, survey methodology, data collection, and data analysis methods.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 030945428X
Category : Social Science
Languages : en
Pages : 151
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Book Description
Federal government statistics provide critical information to the country and serve a key role in a democracy. For decades, sample surveys with instruments carefully designed for particular data needs have been one of the primary methods for collecting data for federal statistics. However, the costs of conducting such surveys have been increasing while response rates have been declining, and many surveys are not able to fulfill growing demands for more timely information and for more detailed information at state and local levels. Innovations in Federal Statistics examines the opportunities and risks of using government administrative and private sector data sources to foster a paradigm shift in federal statistical programs that would combine diverse data sources in a secure manner to enhance federal statistics. This first publication of a two-part series discusses the challenges faced by the federal statistical system and the foundational elements needed for a new paradigm.
Author: Paul P. Biemer
Publisher: John Wiley & Sons
ISBN: 1119041678
Category : Social Science
Languages : en
Pages : 624
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Book Description
Featuring a timely presentation of total survey error (TSE), this edited volume introduces valuable tools for understanding and improving survey data quality in the context of evolving large-scale data sets This book provides an overview of the TSE framework and current TSE research as related to survey design, data collection, estimation, and analysis. It recognizes that survey data affects many public policy and business decisions and thus focuses on the framework for understanding and improving survey data quality. The book also addresses issues with data quality in official statistics and in social, opinion, and market research as these fields continue to evolve, leading to larger and messier data sets. This perspective challenges survey organizations to find ways to collect and process data more efficiently without sacrificing quality. The volume consists of the most up-to-date research and reporting from over 70 contributors representing the best academics and researchers from a range of fields. The chapters are broken out into five main sections: The Concept of TSE and the TSE Paradigm, Implications for Survey Design, Data Collection and Data Processing Applications, Evaluation and Improvement, and Estimation and Analysis. Each chapter introduces and examines multiple error sources, such as sampling error, measurement error, and nonresponse error, which often offer the greatest risks to data quality, while also encouraging readers not to lose sight of the less commonly studied error sources, such as coverage error, processing error, and specification error. The book also notes the relationships between errors and the ways in which efforts to reduce one type can increase another, resulting in an estimate with larger total error. This book: • Features various error sources, and the complex relationships between them, in 25 high-quality chapters on the most up-to-date research in the field of TSE • Provides comprehensive reviews of the literature on error sources as well as data collection approaches and estimation methods to reduce their effects • Presents examples of recent international events that demonstrate the effects of data error, the importance of survey data quality, and the real-world issues that arise from these errors • Spans the four pillars of the total survey error paradigm (design, data collection, evaluation and analysis) to address key data quality issues in official statistics and survey research Total Survey Error in Practice is a reference for survey researchers and data scientists in research areas that include social science, public opinion, public policy, and business. It can also be used as a textbook or supplementary material for a graduate-level course in survey research methods.
Author: Shawn Cole
Publisher: Abdul Latif Jameel Poverty Action Lab
ISBN: 9781736021606
Category :
Languages : en
Pages : 618
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Book Description
This Handbook intends to inform Data Providers and researchers on how to provide privacy-protected access to, handle, and analyze administrative data, and to link them with existing resources, such as a database of data use agreements (DUA) and templates. Available publicly, the Handbook will provide guidance on data access requirements and procedures, data privacy, data security, property rights, regulations for public data use, data architecture, data use and storage, cost structure and recovery, ethics and privacy-protection, making data accessible for research, and dissemination for restricted access use. The knowledge base will serve as a resource for all researchers looking to work with administrative data and for Data Providers looking to make such data available.
Author: Asaph Young Chun
Publisher: John Wiley & Sons
ISBN: 1119272068
Category : Mathematics
Languages : en
Pages : 384
Get Book Here
Book Description
ADMINISTRATIVE RECORDS FOR SURVEY METHODOLOGY Addresses the international use of administrative records for large-scale surveys, censuses, and other statistical purposes Administrative Records for Survey Methodology is a comprehensive guide to improving the quality, cost-efficiency, and interpretability of surveys and censuses using administrative data research. Contributions from a team of internationally-recognized experts provide practical approaches for integrating administrative data in statistical surveys, and discuss the methodological issues—including concerns of privacy, confidentiality, and legality—involved in collecting and analyzing administrative records. Numerous real-world examples highlight technological and statistical innovations, helping readers gain a better understanding of both fundamental methods and advanced techniques for controlling data quality reducing total survey error. Divided into four sections, the first describes the basics of administrative records research and addresses disclosure limitation and confidentiality protection in linked data. Section two focuses on data quality and linking methodology, covering topics such as quality evaluation, measuring and controlling for non-consent bias, and cleaning and using administrative lists. The third section examines the use of administrative records in surveys and includes case studies of the Swedish register-based census and the administrative records applications used for the US 2020 Census. The book’s final section discusses combining administrative and survey data to improve income measurement, enhancing health surveys with data linkage, and other uses of administrative data in evidence-based policymaking. This state-of-the-art resource: Discusses important administrative data issues and suggests how administrative data can be integrated with more traditional surveys Describes practical uses of administrative records for evidence-driven decisions in both public and private sectors Emphasizes using interdisciplinary methodology and linking administrative records with other data sources Explores techniques to leverage administrative data to improve the survey frame, reduce nonresponse follow-up, assess coverage error, measure linkage non-consent bias, and perform small area estimation. Administrative Records for Survey Methodology is an indispensable reference and guide for statistical researchers and methodologists in academia, industry, and government, particularly census bureaus and national statistical offices, and an ideal supplemental text for undergraduate and graduate courses in data science, survey methodology, data collection, and data analysis methods.
Author: Craig A. Hill
Publisher: John Wiley & Sons
ISBN: 1118976320
Category : Social Science
Languages : en
Pages : 784
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Book Description
Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.
Author: Christopher D. Carroll
Publisher: University of Chicago Press
ISBN: 022612665X
Category : Business & Economics
Languages : en
Pages : 517
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Book Description
Robust and reliable measures of consumer expenditures are essential for analyzing aggregate economic activity and for measuring differences in household circumstances. Many countries, including the United States, are embarking on ambitious projects to redesign surveys of consumer expenditures, with the goal of better capturing economic heterogeneity. This is an appropriate time to examine the way consumer expenditures are currently measured, and the challenges and opportunities that alternative approaches might present. Improving the Measurement of Consumer Expenditures begins with a comprehensive review of current methodologies for collecting consumer expenditure data. Subsequent chapters highlight the range of different objectives that expenditure surveys may satisfy, compare the data available from consumer expenditure surveys with that available from other sources, and describe how the United States’s current survey practices compare with those in other nations.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309465370
Category : Social Science
Languages : en
Pages : 195
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Book Description
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.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309170389
Category : Social Science
Languages : en
Pages : 537
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Book Description
This volume, a companion to Evaluating Welfare Reform in an Era of Transition, is a collection of papers on data collection issues for welfare and low-income populations. The papers on survey issues cover methods for designing surveys taking into account nonresponse in advance, obtaining high response rates in telephone surveys, obtaining high response rates in in-person surveys, the effects of incentive payments, methods for adjusting for missing data in surveys of low-income populations, and measurement error issues in surveys, with a special focus on recall error. The papers on administrative data cover the issues of matching and cleaning, access and confidentiality, problems in measuring employment and income, and the availability of data on children. The papers on welfare leavers and welfare dynamics cover a comparison of existing welfare leaver studies, data from the state of Wisconsin on welfare leavers, and data from the National Longitudinal Survey of Youth used to construct measures of heterogeneity in the welfare population based on the recipient's own welfare experience. A final paper discusses qualitative data.
