Administrative Records for Survey Methodology

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Addresses the international use of administrative records for large-scale surveys, censuses, and other statistical purposes Administrative Records for Survey Methodology 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, mesaure linkage non-consent bias, and perform small area estimation.
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Table of Contents

1 Cover

2 Wiley Series in Survey Methodology WILEY SERIES IN SURVEY METHODOLOGY Established in Part by Walter A. Shewhart and Samuel S. Wilks Editors: Mick P. Couper, Graham Kalton, J. N. K. Rao, Norbert Schwarz, Christopher Skinner, Lars Lyberg Editor Emeritus: Robert M. Groves

3 Title Page Administrative Records for Survey Methodology Edited by Asaph Young Chun Statistics Research Institute Statistics Korea, Republic of Korea Michael D. Larsen Department of Mathematics and Statistics Saint Michael’s College, United States Gabriele Durrant Department of Social Statistics and Demography Southampton University, UK Jerome P. Reiter Department of Statistical Science Duke University, United States

4 Copyright

5 Preface

6 Acknowledgments

7 List of Contributors

8 Part I: Fundamentals of Administrative Records Research and Applications 1 On the Use of Proxy Variables in Combining Register and Survey Data 1.1 Introduction 1.2 Instances of Proxy Variable 1.3 Estimation Using Multiple Proxy Variables 1.4 Summary References 2 Disclosure Limitation and Confidentiality Protection in Linked Data 2.1 Introduction 2.2 Paradigms of Protection 2.3 Confidentiality Protection in Linked Data: Examples 2.4 Physical and Legal Protections 2.5 Conclusions 2.A Appendix: Technical Terms and Acronyms Acknowledgments References

9 Part II: Data Quality of Administrative Records and Linking Methodology 3 Evaluation of the Quality of Administrative Data Used in the Dutch Virtual Census 3.1 Introduction 3.2 Data Sources and Variables 3.3 Quality Framework 3.4 Quality Evaluation Results for the Dutch 2011 Census 3.5 Summary 3.6 Practical Implications for Implementation with Surveys and Censuses 3.7 Exercises References 4 Improving Input Data Quality in Register-Based Statistics: The Norwegian Experience 4.1 Introduction 4.2 The Use of Administrative Sources in Statistics Norway 4.3 Managing Statistical Populations 4.4 Experiences from the First Norwegian Purely Register-Based Population and Housing Census of 2011 4.5 The Contact with the Owners of Administrative Registers Was Put into System 4.6 Measuring and Documenting Input Data Quality 4.7 Summary 4.8 Exercises 4.A Example of a Quality Report for Registered Persons in the Central Population Register References 5 Cleaning and Using Administrative Lists: Enhanced Practices and Computational Algorithms for Record Linkage and Modeling/Editing/Imputation 5.1 Introductory Comments 5.2 Edit/Imputation 5.3 Record Linkage 5.4 Models for Adjusting Statistical Analyses for Linkage Error 5.5 Concluding Remarks 5.6 Issues and Some Related Questions References 6 Assessing Uncertainty When Using Linked Administrative Records 6.1 Introduction 6.2 General Sources of Uncertainty 6.3 Approaches to Accounting for Uncertainty 6.4 Concluding Remarks 6.5 Exercises Acknowledgment References 7 Measuring and Controlling for Non-Consent Bias in Linked Survey and Administrative Data 7.1 Introduction 7.2 Strategies for Measuring Linkage Non-Consent Bias 7.3 Methods for Minimizing Non-Consent Bias at the Survey Design Stage 7.4 Methods for Minimizing Non-Consent Bias at the Survey Analysis Stage 7.5 Summary 7.6 Practical Implications for Implementation with Surveys and Censuses 7.7 Exercises References

10 Part III: Use of Administrative Records in Surveys 8 A Register-Based Census: The Swedish Experience 8.1 Introduction 8.2 Background 8.3 Census 2011 8.4 A Register-Based Census 8.5 Evaluation of the Census 8.6 Impact on Population and Housing Statistics 8.7 Summary and Final Remarks References 9 Administrative Records Applications for the 2020 Census 9.1 Introduction 9.2 Administrative Record Usage in the U.S. Census 9.3 Administrative Record Integration in 2020 Census Research 9.4 Quality Assessment 9.5 Other Applications of Administrative Record Usage 9.6 Summary 9.7 Exercises References 10 Use of Administrative Records in Small Area Estimation 10.1 Introduction 10.2 Data Preparation 10.3 Small Area Estimation Models for Combining Information 10.4 An Application 10.5 Concluding Remarks 10.6 Exercises Acknowledgments References

11 Part IV: Use of Administrative Data in Evidence-Based Policymaking 11 Enhancement of Health Surveys with Data Linkage 11.1 Introduction 11.2 Examples of NCHS Health Surveys that Were Enhanced Through Linkage 11.3 NCHS Health Surveys Linked with Vital Records and Administrative Data 11.4 NCHS Data Linkage Program: Linkage Methodology and Processing Issues 11.5 Enhancements to Health Survey Data Through Linkage 11.6 Analytic Considerations and Limitations of Administrative Data 11.7 Future of the NCHS Data Linkage Program 11.8 Exercises Acknowledgments Disclaimer References 12 Combining Administrative and Survey Data to Improve Income Measurement 12.1 Introduction 12.2 Measuring and Decomposing Total Survey Error 12.3 Generalized Coverage Error 12.4 Item Nonresponse and Imputation Error 12.5 Measurement Error 12.6 Illustration: Using Data Linkage to Better Measure Income and Poverty 12.7 Accuracy of Links and the Administrative Data 12.8 Conclusions 12.9 Exercises Acknowledgments References 13 Combining Data from Multiple Sources to Define a Respondent: The Case of Education Data 13.1 Introduction 13.2 Literature Review 13.3 Methodology 13.4 Example of Defining a Unit Respondent for the National Postsecondary Student Aid Study (NPSAS) 13.5 Discussion: Advantages and Disadvantages of Two Approaches to Defining a Unit Respondent 13.6 Practical Implications for Implementation with Surveys and Censuses 13.A Appendix 13.B Appendix References Index End User License Agreement

List of Figures

1 Chapter 1 Figure 1.1Second phase of integrated statistical micro data.

2 Chapter 2 Figure 2.1Probability density function of the ramp distribution used in LEH... Figure 2.2Distribution of Δ B in Maryland. For details, see text.

3 Chapter 3 Figure 3.1 Educational attainment and place of residence by per five-year age... Figure 3.2 Tableplot visualization of age, highest level of education, and cu...

4 Chapter 5 Figure 5.1Log frequency versus weight matches and nonmatches combined. Figure 5.2Comparison of error rate estimation procedures of Winkler (2006a,...

5 Chapter 8 Figure 8.1Registers and links in the system of registers. Figure 8.2Notation for a J*J -table.

6 Chapter 9 Figure 9.12016 NRFU contact strategy for administrative record cases.

7 Chapter 10 Figure 10.1CPS poverty rates for school-aged children plotted against (a) I... Figure 10.2Model diagnostic plots: (a) Standardized residuals plotted again... Figure 10.3Model predictors versus direct estimates for 1993 school-aged ch... Figure 10.4Ratios of standard errors (a) and of coefficients of variation (...

8 Chapter 11 Figure 12.1Illustration of the temporal nature of the linked data using the...

9 Chapter 12 Figure 13.1TSE components in percent of average dollars paid and as shares ... Figure 13.2Error rates in reported receipt of SNAP and public assistance in...

10 Chapter 13 Figure 14.1Comparison of point estimates using the interview weight and the... Figure 14.2Comparison of variance estimates using the interview weight and ...

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