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Data Quality and Record Linkage Techniques

By Thomas N. Herzog , Fritz J. Scheuren , William E. Winkler

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This book offers a practical advice on improving data quality through editing, imputation, and record linkage. The first part of the book deals with methods and models, while the second presents case studies in which these techniques are applied.

Full Description

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  • ISBN13: 978-0-3876-9502-0
  • 244 Pages
  • User Level: Professionals
  • Publication Date: May 23, 2007
  • Available eBook Formats: PDF
Full Description
This book helps practitioners gain a deeper understanding, at an applied level, of the issues involved in improving data quality through editing, imputation, and record linkage. The first part of the book deals with methods and models. Here, we focus on the Fellegi-Holt edit-imputation model, the Little-Rubin multiple-imputation scheme, and the Fellegi-Sunter record linkage model. Brief examples are included to show how these techniques work. In the second part of the book, the authors present real-world case studies in which one or more of these techniques are used. They cover a wide variety of application areas. These include mortgage guarantee insurance, medical, biomedical, highway safety, and social insurance as well as the construction of list frames and administrative lists. Readers will find this book a mixture of practical advice, mathematical rigor, management insight and philosophy. The long list of references at the end of the book enables readers to delve more deeply into the subjects discussed here. The authors also discuss the software that has been developed to apply the techniques described in our text.
Table of Contents

Table of Contents

  1. Introduction.
  2. What is Data Quality and Why Should We Care?.
  3. Examples of Companies Using Data to their Advantage/Disadvantage.
  4. Properties of Data Quality and Metrics for Measuring it.
  5. Basic Data Quality Tools.
  6. Mathematical Preliminaries for Specialized Data Quality Techniques.
  7. Automatic Editing and Imputation of Survey Data
  8. A Unified Approach to Identifying and Correcting Data Problems in Sample Surveys.
  9. Record Linkage
  10. Methodology.
  11. Estimating the Parameters of Fellegi
  12. Sunter Record Linkage Model.
  13. Standardization and Parsing.
  14. Phonetic Coding Systems for Names and/Or Addresses.
  15. Blocking.
  16. String Comparator Metrics for Typographical Error.
  17. Record Linkage Case Studies
  18. Duplicate FHA Single
  19. Family Mortgage Records.
  20. Record Linkage Case Studies
  21. Medical, Biomedical, and Highway Safety.
  22. Constructing List Frames and Administrative Lists.
  23. Social Security and Related Topics.
  24. Confidentiality: Maximizing Public Access to Microdata While Protecting Respondent Privacy.
  25. Review of Record
  26. Linkage Software Products.
  27. Concluding Thoughts on Record Linkage Techniques.

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