Administrative Records for Survey Methodology 1st Edition – Ebook Instant Download/Delivery ISBN(s): 9781119272045,1119272041,9781119272069, 1119272068
Product details:
- ISBN-10: 1119272068
- ISBN-13: 9781119272069
- Author: Asaph Young Chun, Gabriele Durrant, Jerome P. Reiter, Michael D. Larsen
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.
Table contents:
Part I Fundamentals of Administrative Records Research and Applications
1 On the Use of Proxy Variables in Combining Register and Survey Data
2 Disclosure Limitation and Confidentiality Protection in Linked Data
Part II Data Quality of Administrative Records and Linking Methodology
3 Evaluation of the Quality of Administrative Data Used in the Dutch Virtual Census
4 Improving Input Data Quality in Register-Based Statistics: The Norwegian Experience
5 Cleaning and Using Administrative Lists: Enhanced Practices and Computational Algorithms for Record Linkage and Modeling/Editing/Imputation
6 Assessing Uncertainty When Using Linked Administrative Records
7 Measuring and Controlling for Non-Consent Bias in Linked Survey and Administrative Data
Part III Use of Administrative Records in Surveys
8 A Register-Based Census: The Swedish Experience
9 Administrative Records Applications for the 2020 Census
10 Use of Administrative Records in Small Area Estimation
Part IV Use of Administrative Data in Evidence-Based Policymaking
11 Enhancement of Health Surveys with Data Linkage
12 Combining Administrative and Survey Data to Improve Income Measurement
13 Combining Data from Multiple Sources to Define a Respondent: The Case of Education Data
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