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E-raamat: Data Quality and Record Linkage Techniques

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  • Formaat: PDF+DRM
  • Ilmumisaeg: 23-May-2007
  • Kirjastus: Springer-Verlag New York Inc.
  • Keel: eng
  • ISBN-13: 9780387695051
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Data Quality and Record Linkage TechniquesSuurem pilt
  • Formaat: PDF+DRM
  • Ilmumisaeg: 23-May-2007
  • Kirjastus: Springer-Verlag New York Inc.
  • Keel: eng
  • ISBN-13: 9780387695051
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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.

This book helps practitioners gain a working 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. Brief examples are included to show how these techniques work. The second part of the book presents real-world case studies in which one or more of these techniques are applied. These cover a wide variety of application areas, including mortgage guarantee insurance, medical, biomedical, highway safety, and social insurance as well as the construction of list frames and administrative lists. The authors also discuss software that has been developed to apply the techniques described here.Readers will find in this book a mixture of practical advice, mathematical rigor, management insight and philosophy.

Arvustused

From the reviews:



"Data Quality and Record Linkage Techniques is a landmark publication that will facilitate the work of actuaries and other statistical professionals." Douglas C. Borton for The Actuarial Digest



"This book is intended as a primer on editing, imputation and record linkage for analysts who are responsible for the quality of large databases. The book provides an extended bibliography with references . The examples given in the book can be valuable for organizations responsible for the quality of databases, in particular when these databases are constructed by linking several different data sources." (T. de Waal, Kwantitatieve Methoden, October, 2007)



"Tom Herzog has a history of writing books...that most mathematically literate people believe they already understand pretty well--until they read the book....This book...[ is] interesting and informative. Anyone who works with large databases should read it." (Bruce D. Schoebel, Contingencies, Jan/Feb 2008)



"Who should read this book? The short answer is everyone who is concerned about data quality and what can be done to improve it. Buy a copy for yourself; buy another copy for your IT support." (Kevin Pledge, CompAct, October 2007)



"Data Quality and Record Linkage Techniques is one of the few books on data quality and record linkage that try to cover and discuss the possible errors in different types of data in practical situations. The intended audience consists of actuaries, economists, statisticians and computer scientists. This is a good short book for an overview of data quality problems and record linkage techniques. Statisticians, data analysts and indeed anyone who is going to collect data should first read this book ." (Waqas Ahmed Malik and Antony Unwin, Psychometrika, Vol. 73 (1), 2008)



"This book covers two related and important topics: data quality and recordlinkage. case studies are the books major strength; they contain a treasure trove of useful guidelines and tips. For that reason, the book is an excellent purchase for practitioners in business, government, and research settings who plan to undertake major data collection or record linkage efforts. serves as a stand-alone resource on record linkage techniques. The book is aimed squarely at practitioners." (Jerome Reiter, Journal of the American Statistical Association, Vol. 103 (482), 2008)



"The book provides a good, sound, verbal introduction and summary, and a useful point of departure into the more technical side of database quality and record linkage problems. In summary, it should be a core sourcebook for non-mathematical statisticians in official statistics agencies, and database designers and managers in government and commerce. It also provides a useful introduction to this important topic, and a comprehensive reference list for further study, for professional statisticians and academics." (Stephan Haslett, International Statistical Reviews, Vol. 76 (2), 2008)

Preface v
About the Authors xiii
1. Introduction 1
1.1. Audience and Objective
1
1.2. Scope
1
1.3. Structure
2
PART 1 DATA QUALITY: WHAT IT IS, WHY IT IS IMPORTANT, AND HOW TO ACHIEVE IT
2. What Is Data Quality and Why Should We Care?
7
2.1. When Are Data of High Quality?
7
2.2. Why Care About Data Quality?
10
2.3. How Do You Obtain High-Quality Data?
11
2.4. Practical Tips
13
2.5. Where Are We Now?
13
3. Examples of Entities Using Data to their Advantage/Disadvantage
17
3.1. Data Quality as a Competitive Advantage
17
3.2. Data Quality Problems and their Consequences
20
3.3. How Many People Really Live to 100 and Beyond? Views from the United States, Canada, and the United Kingdom
25
3.4. Disabled Airplane Pilots – A Successful Application of Record Linkage
26
3.5. Completeness and Accuracy of a Billing Database: Why It Is Important to the Bottom Line
26
3.6. Where Are We Now?
27
4. Properties of Data Quality and Metrics for Measuring It
29
4.1. Desirable Properties of Databases/Lists
29
4.2. Examples of Merging Two or More Lists and the Issues that May Arise
31
4.3. Metrics Used when Merging Lists
33
4.4. Where Are We Now?
35
5. Basic Data Quality Tools
37
5.1. Data Elements
37
5.2. Requirements Document
38
5.3. A Dictionary of Tests
39
5.4. Deterministic Tests
40
5.5. Probabilistic Tests
44
5.6. Exploratory Data Analysis Techniques
44
5.7. Minimizing Processing Errors
46
5.8. Practical Tips
46
5.9. Where Are We Now?
48
PART 2 SPECIALIZED TOOLS FOR DATABASE IMPROVEMENT
6. Mathematical Preliminaries for Specialized Data Quality Techniques
51
6.1. Conditional Independence
51
6.2. Statistical Paradigms
53
6.3. Capture—Recapture Procedures and Applications
54
7. Automatic Editing and Imputation of Sample Survey Data
61
7.1. Introduction
61
7.2. Early Editing Efforts
63
7.3. Fellegi—Holt Model for Editing
64
7.4. Practical Tips
65
7.5. Imputation
66
7.6. Constructing a Unified Edit/Imputation Model
71
7.7. Implicit Edits — A Key Construct of Editing Software
73
7.8. Editing Software
75
7.9. Is Automatic Editing Taking Up Too Much Time and Money?
78
7.10. Selective Editing
79
7.11. Tips on Automatic Editing and Imputation
79
7.12. Where Are We Now?
80
8. Record Linkage — Methodology
81
8.1. Introduction
81
8.2. Why Did Analysts Begin Linking Records?
82
8.3. Deterministic Record Linkage
82
8.4. Probabilistic Record Linkage — A Frequentist Perspective
83
8.5. Probabilistic Record Linkage — A Bayesian Perspective
91
8.6. Where Are We Now?
92
9. Estimating the Parameters of the Fellegi–Sunter Record Linkage Model
93
9.1. Basic Estimation of Parameters Under Simple Agreement/Disagreement Patterns
93
9.2. Parameter Estimates Obtained via Frequency-Based Matching
94
9.3. Parameter Estimates Obtained Using Data from Current Files
96
9.4. Parameter Estimates Obtained via the EM Algorithm
97
9.5. Advantages and Disadvantages of Using the EM Algorithm to Estimate m- and u-probabilities
101
9.6. General Parameter Estimation Using the EM Algorithm
103
9.7. Where Are We Now?
106
10. Standardization and Parsing
107
10.1. Obtaining and Understanding Computer Files
109
10.2. Standardization of Terms
110
10.3. Parsing of Fields
111
10.4. Where Are We Now?
114
11. Phonetic Coding Systems for Names
115
11.1. Soundex System of Names
115
11.2. NYSIIS Phonetic Decoder
119
11.3. Where Are We Now?
121
12. Blocking
123
12.1. Independence of Blocking Strategies
124
12.2. Blocking Variables
125
12.3. Using Blocking Strategies to Identify Duplicate List Entries
126
12.4. Using Blocking Strategies to Match Records Between Two Sample Surveys
128
12.5. Estimating the Number of Matches Missed
130
12.6. Where Are We Now?
130
13. String Comparator Metrics for Typographical Error
131
13.1. Jaro String Comparator Metric for Typographical Error
131
13.2. Adjusting the Matching Weight for the Jaro String Comparator
133
13.3. Winkler String Comparator Metric for Typographical Error
133
13.4. Adjusting the Weights for the Winkler Comparator Metric
134
13.5. Where are We Now?
135
PART 3 RECORD LINKAGE CASE STUDIES
14. Duplicate FHA Single-Family Mortgage Records: A Case Study of Data Problems, Consequences, and Corrective Steps
139
14.1. Introduction
139
14.2. FHA Case Numbers on Single-Family Mortgages
141
14.3. Duplicate Mortgage Records
141
14.4. Mortgage Records with an Incorrect Termination Status
145
14.5. Estimating the Number of Duplicate Mortgage Records
148
15. Record Linkage Case Studies in the Medical, Biomedical, and Highway Safety Areas
151
15.1. Biomedical and Genetic Research Studies
151
15.2. Who goes to a Chiropractor?
153
15.3. National Master Patient Index
154
15.4. Provider Access to Immunization Register Securely (PAiRS) System
155
15.5. Studies Required by the Intermodal Surface Transportation Efficiency Act of 1991
156
15.6. Crash Outcome Data Evaluation System
157
16. Constructing List Frames and Administrative Lists
159
16.1. National Address Register of Residences in Canada
160
16.2. USDA List Frame of Farms in the United States
162
16.3. List Frame Development for the US Census of Agriculture
165
16.4. Post-enumeration Studies of US Decennial Census
166
17. Social Security and Related Topics
169
17.1. Hidden Multiple Issuance of Social Security Numbers
169
17.2. How Social Security Stops Benefit Payments after Death
173
17.3. CPS–IRS–SSA Exact Match File
175
17.4. Record Linkage and Terrorism
177
PART 4 OTHER TOPICS
18. Confidentiality: Maximizing Access to Micro-data while Protecting Privacy
181
18.1. Importance of High Quality of Data in the Original File
182
18.2. Documenting Public-use Files
183
18.3. Checking Re-identifiability
183
18.4. Elementary Masking Methods and Statistical Agencies
186
18.5. Protecting Confidentiality of Medical Data
193
18.6. More-advanced Masking Methods – Synthetic Datasets
195
18.7. Where Are We Now?
198
19. Review of Record Linkage Software
201
19.1. Government
201
19.2. Commercial
202
19.3. Checklist for Evaluating Record Linkage Software
203
20. Summary
Chapter
209
Bibliography 211
Index 221


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