Administrative Records for Survey Methodology
(Sprache: Englisch)
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...
Addresses the international use of administrative records for large-scale surveys, censuses, and other statistical purposes
Administrative Records for Survey Methodology is a comprehensive...
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Klappentext zu „Administrative Records for Survey Methodology “
ADMINISTRATIVE RECORDS FOR SURVEY METHODOLOGYAddresses 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
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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.
* 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.
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Inhaltsverzeichnis zu „Administrative Records for Survey Methodology “
Preface xvAcknowledgments xxi
List of Contributors xxiii
Part I Fundamentals of Administrative Records Research and Applications 1
1 On the Use of Proxy Variables in Combining Register and Survey Data 3
Li-Chun Zhang
1.1 Introduction 3
1.1.1 A Multisource Data Perspective 3
1.1.2 Concept of Proxy Variable 5
1.2 Instances of Proxy Variable 7
1.2.1 Representation 7
1.2.2 Measurement 10
1.3 Estimation Using Multiple Proxy Variables 12
1.3.1 Asymmetric Setting 13
1.3.2 Uncertainty Evaluation: A Case of Two-Way Data 15
1.3.3 Symmetric Setting 17
1.4 Summary 20
References 20
2 Disclosure Limitation and Confidentiality Protection in Linked Data 25
John M. Abowd, Ian M. Schmutte, and Lars Vilhuber
2.1 Introduction 25
2.2 Paradigms of Protection 27
2.2.1 Input Noise Infusion 29
2.2.2 Formal Privacy Models 30
2.3 Confidentiality Protection in Linked Data: Examples 32
2.3.1 HRS-SSA 32
2.3.1.1 Data Description 32
2.3.1.2 Linkages to Other Data 32
2.3.1.3 Disclosure Avoidance Methods 33
2.3.2 SIPP-SSA-IRS (SSB) 34
2.3.2.1 Data Description 34
2.3.2.2 Disclosure Avoidance Methods 35
2.3.2.3 Disclosure Avoidance Assessment 35
2.3.2.4 Analytical Validity Assessment 37
2.3.3 LEHD: Linked Establishment and Employee Records 38
2.3.3.1 Data Description 38
2.3.3.2 Disclosure Avoidance Methods 39
2.3.3.3 Disclosure Avoidance Assessment for QWI 41
2.3.3.4 Analytical Validity Assessment for QWI 42
2.4 Physical and Legal Protections 43
2.4.1 Statistical Data Enclaves 44
2.4.2 Remote Processing 46
2.4.3 Licensing 46
2.4.4 Disclosure Avoidance Methods 47
2.4.5 Data Silos 48
2.5 Conclusions 49
2.A.1
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Other Abbreviations 51
2.A.2 Concepts 52
Acknowledgments 54
References 54
Part II Data Quality of Administrative Records and Linking Methodology 61
3 Evaluation of the Quality of Administrative Data Used in the Dutch Virtual Census 63
Piet Daas, Eric S. Nordholt, Martijn Tennekes, and Saskia Ossen
3.1 Introduction 63
3.2 Data Sources and Variables 64
3.3 Quality Framework 66
3.3.1 Source and Metadata Hyper Dimensions 66
3.3.2 Data Hyper Dimension 68
3.4 Quality Evaluation Results for the Dutch 2011 Census 69
3.4.1 Source and Metadata: Application of Checklist 69
3.4.2 Data Hyper Dimension: Completeness and Accuracy Results 72
3.4.2.1 Completeness Dimension 73
3.4.2.2 Accuracy Dimension 75
3.4.2.3 Visualizing with a Tableplot 78
3.4.3 Discussion of the Quality Findings 80
3.5 Summary 81
3.6 Practical Implications for Implementation with Surveys and Censuses 81
3.7 Exercises 82
References 82
4 Improving Input Data Quality in Register-Based Statistics: The Norwegian Experience 85
Coen Hendriks
4.1 Introduction 85
4.2 The Use of Administrative Sources in Statistics Norway 86
4.3 Managing Statistical Populations 89
4.4 Experiences from the First Norwegian Purely Register-Based Population and Housing Census of 2011 91
4.5 The Contact with the Owners of Administrative Registers Was Put into System 93
4.5.1 Agreements on Data Processing 93
4.5.2 Agreements of Cooperation on Data Quality in Administrative Data Systems 95
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2.A.2 Concepts 52
Acknowledgments 54
References 54
Part II Data Quality of Administrative Records and Linking Methodology 61
3 Evaluation of the Quality of Administrative Data Used in the Dutch Virtual Census 63
Piet Daas, Eric S. Nordholt, Martijn Tennekes, and Saskia Ossen
3.1 Introduction 63
3.2 Data Sources and Variables 64
3.3 Quality Framework 66
3.3.1 Source and Metadata Hyper Dimensions 66
3.3.2 Data Hyper Dimension 68
3.4 Quality Evaluation Results for the Dutch 2011 Census 69
3.4.1 Source and Metadata: Application of Checklist 69
3.4.2 Data Hyper Dimension: Completeness and Accuracy Results 72
3.4.2.1 Completeness Dimension 73
3.4.2.2 Accuracy Dimension 75
3.4.2.3 Visualizing with a Tableplot 78
3.4.3 Discussion of the Quality Findings 80
3.5 Summary 81
3.6 Practical Implications for Implementation with Surveys and Censuses 81
3.7 Exercises 82
References 82
4 Improving Input Data Quality in Register-Based Statistics: The Norwegian Experience 85
Coen Hendriks
4.1 Introduction 85
4.2 The Use of Administrative Sources in Statistics Norway 86
4.3 Managing Statistical Populations 89
4.4 Experiences from the First Norwegian Purely Register-Based Population and Housing Census of 2011 91
4.5 The Contact with the Owners of Administrative Registers Was Put into System 93
4.5.1 Agreements on Data Processing 93
4.5.2 Agreements of Cooperation on Data Quality in Administrative Data Systems 95
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Autoren-Porträt von Asaph Young Chun, Michael D. Larsen
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.
Bibliographische Angaben
- Autoren: Asaph Young Chun , Michael D. Larsen
- 2021, 1. Auflage, 384 Seiten, Maße: 15,1 x 23,7 cm, Gebunden, Englisch
- Herausgegeben: Asaph Young Chun, Michael D. Larsen, Gabriele Durrant, Jerome P. Reiter
- Verlag: Wiley & Sons
- ISBN-10: 1119272041
- ISBN-13: 9781119272045
Sprache:
Englisch
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