Administrative Records for Survey Methodology - (Wiley Survey Methodology) (Hardcover)

About the Book

"Featuring contributions from well-known international experts, this book addresses the methodological issues involved in administrative data research as well as the various concerns users face with administrative records such as issues of privacy, confidentiality, and legality. The book illustrates numerous real-world examples of administrative data research from various countries, culminating in a comprehensive guide to administrative data in statistical surveys. This historical and international perspective provides readers with a better understanding of the practical applications and approaches needed for improving the quality of surveys, controlling the cost of survey data collection, and integrating administrative data with other data obtained from surveys and censuses. This book also features detailed coverage on the advanced statistical techniques for the control of data quality and reduction in total survey error. The first part of the book focuses on the theory of total administrative records error and provides relevant practices case studies tied to the survey life-cycle, while the second part of the book features the technical issues of processing and linking administrative data with multiple sources of data in multimode data collection. Bayesian approaches are linked to real-world applications for the use of administrative data in surveys and censuses over the survey life cycle, and the relevance of how these cutting-edge techniques can affect administrative records research is illustrated in key sectors of health, economy, and education. In addition, these technological and statistical innovations are used to advance the systematic integration of administrative data, improve the survey frame, reduce nonresponse follow-up, and assess coverage error. Topical coverage includes: pandata systems to enhance survey and census systems; integration of survey and administrative data for statistical purposes; evaluation of the quality of administrative data; measurement of data quality in register-based statistics; cleaning and using administrative lists; assessing uncertainty; record linkage and assessment of date in health sciences; methods to improve small area estimation; administrative records for imputing nonresponse; Bayesian use of administrative records around census life cycle; use of administrative data in official statistics; application of administrative data in health science; using linking survey and administrative data to improve economic surveys; and administrative sources for censuses with demographic and social statistics"--

Book Synopsis

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.

From the Back Cover

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.

About the Author

Asaph Young Chun, PhD, is Director-General, Statistics Research Institute, Statistics Korea, Republic of Korea.

Michael D. Larsen, PhD, is Professor and Chair, Department of Mathematics and Statistics, Saint Michael's College, Vermont, USA.

Gabriele Durrant, PhD, is Professor, Department of Social Statistics and Demography, University of Southampton, UK.

Jerome P. Reiter, PhD, is Professor and Chair, Department of Statistical Science, Duke University, North Carolina, USA.