Administrative Records for Survey Methodology

Author:   Asaph Young Chun (Statistics Research Institute, Korea) ,  Michael D. Larsen (Saint Michael's College, United States) ,  Gabriele Durrant (Southampton University, UK) ,  Jerome P. Reiter (Duke University, United States)
Publisher:   John Wiley & Sons Inc
ISBN:  

9781119272045


Pages:   384
Publication Date:   15 June 2021
Format:   Hardback
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

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Administrative Records for Survey Methodology


Overview

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.

Full Product Details

Author:   Asaph Young Chun (Statistics Research Institute, Korea) ,  Michael D. Larsen (Saint Michael's College, United States) ,  Gabriele Durrant (Southampton University, UK) ,  Jerome P. Reiter (Duke University, United States)
Publisher:   John Wiley & Sons Inc
Imprint:   John Wiley & Sons Inc
Dimensions:   Width: 1.00cm , Height: 1.00cm , Length: 1.00cm
Weight:   0.454kg
ISBN:  

9781119272045


ISBN 10:   1119272041
Pages:   384
Publication Date:   15 June 2021
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of stock   Availability explained
The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available.

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Author Information

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.

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