Data Linkages And Models

Author : Katie Harron,Harvey Goldstein,Chris Dibben
Publisher : John Wiley & Sons
Page : 288 pages
File Size : 47,6 Mb
Release : 2015-09-22
Category : Medical
ISBN : 9781119072485

Get Book

Methodological Developments in Data Linkage by Katie Harron,Harvey Goldstein,Chris Dibben Pdf

A comprehensive compilation of new developments in data linkage methodology The increasing availability of large administrative databases has led to a dramatic rise in the use of data linkage, yet the standard texts on linkage are still those which describe the seminal work from the 1950-60s, with some updates. Linkage and analysis of data across sources remains problematic due to lack of discriminatory and accurate identifiers, missing data and regulatory issues. Recent developments in data linkage methodology have concentrated on bias and analysis of linked data, novel approaches to organising relationships between databases and privacy-preserving linkage. Methodological Developments in Data Linkage brings together a collection of contributions from members of the international data linkage community, covering cutting edge methodology in this field. It presents opportunities and challenges provided by linkage of large and often complex datasets, including analysis problems, legal and security aspects, models for data access and the development of novel research areas. New methods for handling uncertainty in analysis of linked data, solutions for anonymised linkage and alternative models for data collection are also discussed. Key Features: Presents cutting edge methods for a topic of increasing importance to a wide range of research areas, with applications to data linkage systems internationally Covers the essential issues associated with data linkage today Includes examples based on real data linkage systems, highlighting the opportunities, successes and challenges that the increasing availability of linkage data provides Novel approach incorporates technical aspects of both linkage, management and analysis of linked data This book will be of core interest to academics, government employees, data holders, data managers, analysts and statisticians who use administrative data. It will also appeal to researchers in a variety of areas, including epidemiology, biostatistics, social statistics, informatics, policy and public health.

Author : Kenneth Hanson
Publisher : Unknown
Page : 44 pages
File Size : 52,6 Mb
Release : 1989
Category : Equilibrium (Economics)
ISBN : UIUC:30112003277917

Get Book

Data, Linkages, and Models by Kenneth Hanson Pdf

Author : Thomas N. Herzog,Fritz J. Scheuren,William E. Winkler
Publisher : Springer Science & Business Media
Page : 234 pages
File Size : 43,9 Mb
Release : 2007-05-23
Category : Computers
ISBN : 9780387695051

Get Book

Data Quality and Record Linkage Techniques by Thomas N. Herzog,Fritz J. Scheuren,William E. Winkler Pdf

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.

Author : Nuno Crato,Paolo Paruolo
Publisher : Springer
Page : 346 pages
File Size : 53,5 Mb
Release : 2018-10-02
Category : Political Science
ISBN : 9783319784618

Get Book

Data-Driven Policy Impact Evaluation by Nuno Crato,Paolo Paruolo Pdf

In the light of better and more detailed administrative databases, this open access book provides statistical tools for evaluating the effects of public policies advocated by governments and public institutions. Experts from academia, national statistics offices and various research centers present modern econometric methods for an efficient data-driven policy evaluation and monitoring, assess the causal effects of policy measures and report on best practices of successful data management and usage. Topics include data confidentiality, data linkage, and national practices in policy areas such as public health, education and employment. It offers scholars as well as practitioners from public administrations, consultancy firms and nongovernmental organizations insights into counterfactual impact evaluation methods and the potential of data-based policy and program evaluation.

Author : National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Committee on National Statistics,Panel on Improving Federal Statistics for Policy and Social Science Research Using Multiple Data Sources and State-of-the-Art Estimation Methods
Publisher : National Academies Press
Page : 195 pages
File Size : 53,7 Mb
Release : 2018-01-27
Category : Social Science
ISBN : 9780309465373

Get Book

Federal Statistics, Multiple Data Sources, and Privacy Protection by National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Committee on National Statistics,Panel on Improving Federal Statistics for Policy and Social Science Research Using Multiple Data Sources and State-of-the-Art Estimation Methods Pdf

The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.

Author : Peter Christen,Thilina Ranbaduge,Rainer Schnell
Publisher : Unknown
Page : 476 pages
File Size : 49,8 Mb
Release : 2020
Category : Computer security
ISBN : 9783030597061

Get Book

Linking Sensitive Data by Peter Christen,Thilina Ranbaduge,Rainer Schnell Pdf

This book provides modern technical answers to the legal requirements of pseudonymisation as recommended by privacy legislation. It covers topics such as modern regulatory frameworks for sharing and linking sensitive information, concepts and algorithms for privacy-preserving record linkage and their computational aspects, practical considerations such as dealing with dirty and missing data, as well as privacy, risk, and performance assessment measures. Existing techniques for privacy-preserving record linkage are evaluated empirically and real-world application examples that scale to population sizes are described. The book also includes pointers to freely available software tools, benchmark data sets, and tools to generate synthetic data that can be used to test and evaluate linkage techniques. This book consists of fourteen chapters grouped into four parts, and two appendices. The first part introduces the reader to the topic of linking sensitive data, the second part covers methods and techniques to link such data, the third part discusses aspects of practical importance, and the fourth part provides an outlook of future challenges and open research problems relevant to linking sensitive databases. The appendices provide pointers and describe freely available, open-source software systems that allow the linkage of sensitive data, and provide further details about the evaluations presented. A companion Web site at https://dmm.anu.edu.au/lsdbook2020 provides additional material and Python programs used in the book. This book is mainly written for applied scientists, researchers, and advanced practitioners in governments, industry, and universities who are concerned with developing, implementing, and deploying systems and tools to share sensitive information in administrative, commercial, or medical databases. The Book describes how linkage methods work and how to evaluate their performance. It covers all the major concepts and methods and also discusses practical matters such as computational efficiency, which are critical if the methods are to be used in practice - and it does all this in a highly accessible way! David J. Hand, Imperial College, London.

Author : Robin Lovelace,Morgane Dumont
Publisher : CRC Press
Page : 260 pages
File Size : 42,6 Mb
Release : 2017-09-07
Category : Computers
ISBN : 9781315363165

Get Book

Spatial Microsimulation with R by Robin Lovelace,Morgane Dumont Pdf

Generate and Analyze Multi-Level Data Spatial microsimulation involves the generation, analysis, and modeling of individual-level data allocated to geographical zones. Spatial Microsimulation with R is the first practical book to illustrate this approach in a modern statistical programming language. Get Insight into Complex Behaviors The book progresses from the principles underlying population synthesis toward more complex issues such as household allocation and using the results of spatial microsimulation for agent-based modeling. This equips you with the skills needed to apply the techniques to real-world situations. The book demonstrates methods for population synthesis by combining individual and geographically aggregated datasets using the recent R packages ipfp and mipfp. This approach represents the "best of both worlds" in terms of spatial resolution and person-level detail, overcoming issues of data confidentiality and reproducibility. Implement the Methods on Your Own Data Full of reproducible examples using code and data, the book is suitable for students and applied researchers in health, economics, transport, geography, and other fields that require individual-level data allocated to small geographic zones. By explaining how to use tools for modeling phenomena that vary over space, the book enhances your knowledge of complex systems and empowers you to provide evidence-based policy guidance.

Author : Mary E. Burfisher
Publisher : Unknown
Page : 40 pages
File Size : 40,7 Mb
Release : 1992
Category : Agriculture and state
ISBN : UIUC:30112019037867

Get Book

Data Base for a Computable General Equilibrium Model of the Agricultural Sectors of the United States and Mexico and Their Interactions by Mary E. Burfisher Pdf

Author : National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Committee on National Statistics,Panel on Improving Federal Statistics for Policy and Social Science Research Using Multiple Data Sources and State-of-the-Art Estimation Methods
Publisher : National Academies Press
Page : 151 pages
File Size : 48,8 Mb
Release : 2017-04-21
Category : Social Science
ISBN : 9780309454285

Get Book

Innovations in Federal Statistics by National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Committee on National Statistics,Panel on Improving Federal Statistics for Policy and Social Science Research Using Multiple Data Sources and State-of-the-Art Estimation Methods Pdf

Federal government statistics provide critical information to the country and serve a key role in a democracy. For decades, sample surveys with instruments carefully designed for particular data needs have been one of the primary methods for collecting data for federal statistics. However, the costs of conducting such surveys have been increasing while response rates have been declining, and many surveys are not able to fulfill growing demands for more timely information and for more detailed information at state and local levels. Innovations in Federal Statistics examines the opportunities and risks of using government administrative and private sector data sources to foster a paradigm shift in federal statistical programs that would combine diverse data sources in a secure manner to enhance federal statistics. This first publication of a two-part series discusses the challenges faced by the federal statistical system and the foundational elements needed for a new paradigm.

Author : John R. Talburt
Publisher : Elsevier
Page : 256 pages
File Size : 40,5 Mb
Release : 2011-01-14
Category : Computers
ISBN : 0123819733

Get Book

Entity Resolution and Information Quality by John R. Talburt Pdf

Entity Resolution and Information Quality presents topics and definitions, and clarifies confusing terminologies regarding entity resolution and information quality. It takes a very wide view of IQ, including its six-domain framework and the skills formed by the International Association for Information and Data Quality {IAIDQ). The book includes chapters that cover the principles of entity resolution and the principles of Information Quality, in addition to their concepts and terminology. It also discusses the Fellegi-Sunter theory of record linkage, the Stanford Entity Resolution Framework, and the Algebraic Model for Entity Resolution, which are the major theoretical models that support Entity Resolution. In relation to this, the book briefly discusses entity-based data integration (EBDI) and its model, which serve as an extension of the Algebraic Model for Entity Resolution. There is also an explanation of how the three commercial ER systems operate and a description of the non-commercial open-source system known as OYSTER. The book concludes by discussing trends in entity resolution research and practice. Students taking IT courses and IT professionals will find this book invaluable. First authoritative reference explaining entity resolution and how to use it effectively Provides practical system design advice to help you get a competitive advantage Includes a companion site with synthetic customer data for applicatory exercises, and access to a Java-based Entity Resolution program.

Author : Agency for Healthcare Research and Quality/AHRQ
Publisher : Government Printing Office
Page : 396 pages
File Size : 54,9 Mb
Release : 2014-04-01
Category : Medical
ISBN : 9781587634338

Get Book

Registries for Evaluating Patient Outcomes by Agency for Healthcare Research and Quality/AHRQ Pdf

This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.

Author : Andrew Gelman,Xiao-Li Meng
Publisher : John Wiley & Sons
Page : 436 pages
File Size : 51,7 Mb
Release : 2004-10-22
Category : Mathematics
ISBN : 9780470090442

Get Book

Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives by Andrew Gelman,Xiao-Li Meng Pdf

This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real-world examples which do not feature in many standard texts. The book is dedicated to Professor Don Rubin (Harvard). Don Rubin has made fundamental contributions to the study of missing data. Key features of the book include: Comprehensive coverage of an imporant area for both research and applications. Adopts a pragmatic approach to describing a wide range of intermediate and advanced statistical techniques. Covers key topics such as multiple imputation, propensity scores, instrumental variables and Bayesian inference. Includes a number of applications from the social and health sciences. Edited and authored by highly respected researchers in the area.

Author : Noel A. Card,James P. Selig,Todd Little
Publisher : Routledge
Page : 562 pages
File Size : 52,6 Mb
Release : 2011-04-12
Category : Psychology
ISBN : 9781135703936

Get Book

Modeling Dyadic and Interdependent Data in the Developmental and Behavioral Sciences by Noel A. Card,James P. Selig,Todd Little Pdf

This book reviews methods of conceptualizing, measuring, and analyzing interdependent data in developmental and behavioral sciences. Quantitative and developmental experts describe best practices for modeling interdependent data that stem from interactions within families, relationships, and peer groups, for example. Complex models for analyzing longitudinal data, such as growth curves and time series, are also presented. Many contributors are innovators of the techniques and all are able to clearly explain the methodologies and their practical problems including issues of measurement, missing data, power and sample size, and the specific limitations of each method. Featuring a balance between analytic strategies and applications, the book addresses: The Actor-Partner Interdependence Model for analyzing influence between two individuals The Intraclass Correlational Approach for analyzing distinguishable roles (parent-child) or exchangeable (same-sex) dyadic data The Social Relations Model for analyzing group interdependency Social Network Analysis approaches for relationships between individuals This book is intended for graduate students and researchers across the developmental, social, behavioral, and educational sciences. It is an excellent research guide and a valuable resource for advanced methods courses.

Author : National Research Council,Division on Engineering and Physical Sciences,Board on Mathematical Sciences and Their Applications,Committee on Applied and Theoretical Statistics,Committee on the Analysis of Massive Data
Publisher : National Academies Press
Page : 191 pages
File Size : 50,8 Mb
Release : 2013-09-03
Category : Mathematics
ISBN : 9780309287814

Get Book

Frontiers in Massive Data Analysis by National Research Council,Division on Engineering and Physical Sciences,Board on Mathematical Sciences and Their Applications,Committee on Applied and Theoretical Statistics,Committee on the Analysis of Massive Data Pdf

Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.

Author : Institute of Medicine,Board on Health Sciences Policy,Committee on Strategies for Responsible Sharing of Clinical Trial Data
Publisher : National Academies Press
Page : 304 pages
File Size : 49,6 Mb
Release : 2015-04-20
Category : Medical
ISBN : 9780309316323

Get Book

Sharing Clinical Trial Data by Institute of Medicine,Board on Health Sciences Policy,Committee on Strategies for Responsible Sharing of Clinical Trial Data Pdf

Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research--from funders, to researchers, to journals, to physicians, and ultimately, to patients.