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Data Quality and Record Linkage Techniques
This book offers a practical understanding of issues involved in improving data quality through editing, imputation, and record linkage. The first part of the book deals with methods and models, focusing on the Fellegi-Holt edit-imputation model, the Little-Rubin multiple-imputation scheme, and the Fellegi-Sunter record linkage model. The second part presents case studies in which these techniques are applied in a variety of areas, including mortgage guarantee insurance, medical, biomedical, highway safety, and social insurance as well as the construction of list frames and administrative lists. This book offers a mixture of practical advice, mathematical rigor, management insight and philosophy.
John William Winkler
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The State of Record Linkage and Current Research Problems
This paper provides an overview of methods and systems developed for record linkage.
Handbook of Record Linkage Methods
The first text to provide a comprehensive and accessible guide to carrying out record linkage procedures across various fields of research, Handbook of Record Linkage Methods unites key concepts from statistics and computer science with interesting, real–world applications. The authors address the topic in self–contained sections that focus on various aspects of carrying out record linkage procedures. The text also addresses application methods through engaging, real–world examples from US Census Bureau, National Center for Health Statistics as well as the fields of epidemiology, economics, and agriculture.
Advanced Methods for Record Linkage
Record linkage, or computer matching, is needed for the creation and maintenance of name and address lists that support operations for and evaluations of a Year 2000 Census. This paper describes three advances. The first is an enhanced method of string comparisons for dealing with typographical variations and scanning errors. It improves upon string comparators in computer science. The second is a linear assignment algorithm that can use only 0.002 as much storage as existing algorithms in operations research, requires at most an additional 0.03 increase in time, and has less of a tendency to make erroneous matching assignments, than existing sparse-array algorithms because of how it deals w...
