Methodological Developments in Data Linkage PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Methodological Developments in Data Linkage PDF full book. Access full book title Methodological Developments in Data Linkage by Katie Harron. Download full books in PDF and EPUB format.
Author: Katie Harron
Publisher: John Wiley & Sons
ISBN: 1118745876
Category : Medical
Languages : en
Pages : 286
Get Book Here
Book Description
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: Katie Harron
Publisher: John Wiley & Sons
ISBN: 1118745876
Category : Medical
Languages : en
Pages : 286
Get Book Here
Book Description
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: Katie Harron
Publisher: John Wiley & Sons
ISBN: 1119072468
Category : Medical
Languages : en
Pages : 288
Get Book Here
Book Description
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: Sergio Consoli
Publisher: Springer
ISBN: 3030052494
Category : Computers
Languages : en
Pages : 367
Get Book Here
Book Description
This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book.
Author: Craig A. Hill
Publisher: John Wiley & Sons
ISBN: 1118976320
Category : Social Science
Languages : en
Pages : 784
Get Book Here
Book Description
Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data. Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more. Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.
Author: Raymond-Alain Thietart
Publisher: SAGE
ISBN: 1412933625
Category : Business & Economics
Languages : en
Pages : 435
Get Book Here
Book Description
`This book provides refreshing and powerful insights on the challenges of conducting management research from a European perspective. Particulalrly for someone embarking on a managment research career this book will provide valuable guidelines.′ -- Ian MacMillan, Wharton School of Business, University of Pennsylvania `This comprehensive volume is distinguished by its balance and pragmatism. The authors who present the various research methods are not proponents but researchers who have applied these methods. The authors who discuss philosophical and strategic issues are not advocates but researchers who have had to confront these issues in their research′ - Bill Starbuck, New York University `Doing Management Research is a fabulous contribution to our field. Thietart and his colleagues have put together a unique and valuable guide to help management scholars more deeply understand the issues, dynamics and contradictions of executing first class managerial research. This book will hold an important place on the researcher′s desk for years to come′ - Michael Tushman, Harvard Business School ′This is an excellent in-depth examination of the conduct of management research. It will serve as a valuable resource for management scholars and researchers and is a must read for Ph.D. students in management.′ -- Michael Hitt, Arizona State University `This book will prove to be an excellent guide for those engaged in management research for the first time and an excellent refresher for more experienced scholars. Raymond Thietart and his colleagues should be thanked roundly for this comprehensive volume′ - Gordon Walker, Southern Methodist University, Cox Business School `This textbook makes an outstanding contribution to texts on management research. For researchers considering management research it offers an extensive guide to the research process′ - Paula Roberts, Nurse Researcher Doing Management Research, a major new textbook, provides answers to questions and problems which researchers invariably encounter when embarking on management research, be it quantitative or qualitative. This book will carefully guide the reader through the research process from beginning to end. An excellent tool for academics and students, it enables the reader to acquire and build upon empirical evidence, and to decide what tools to use to understand and describe what is being observed, and then, which methods of analysis to adopt. There is an entire section dedicated to writing up and communicating the research findings. Written in an accessible and easy-to-use style, this book can be read from cover to cover or dipped into, to clarify particular issues during the research process. Doing Management Research results from the ′hands-on′ experience of a large group of researchers who have all had to address the different issues raised when undertaking management research. It is anchored in real methodological problems that researchers face in their work. This work will also become one of the most useful reference tools for senior researchers who are looking for answers to epistemological or methodological problems.
Author: Ger Snijkers
Publisher: John Wiley & Sons
ISBN: 1119672309
Category : Business & Economics
Languages : en
Pages : 900
Get Book Here
Book Description
ADVANCES IN BUSINESS STATISTICS, METHODS AND DATA COLLECTION Advances in Business Statistics, Methods and Data Collection delivers insights into the latest state of play in producing establishment statistics, obtained from businesses, farms and institutions. Presenting materials and reflecting discussions from the 6th International Conference on Establishment Statistics (ICES-VI), this edited volume provides a broad overview of methodology underlying current establishment statistics from every aspect of the production life cycle while spotlighting innovative and impactful advancements in the development, conduct, and evaluation of modern establishment statistics programs. Highlights include: Practical discussions on agile, timely, and accurate measurement of rapidly evolving economic phenomena such as globalization, new computer technologies, and the informal sector. Comprehensive explorations of administrative and new data sources and technologies, covering big (organic) data sources and methods for data integration, linking, machine learning and visualization. Detailed compilations of statistical programs’ responses to wide-ranging data collection and production challenges, among others caused by the Covid-19 pandemic. In-depth examinations of business survey questionnaire design, computerization, pretesting methods, experimentation, and paradata. Methodical presentations of conventional and emerging procedures in survey statistics techniques for establishment statistics, encompassing probability sampling designs and sample coordination, non-probability sampling, missing data treatments, small area estimation and Bayesian methods. Providing a broad overview of most up-to-date science, this book challenges the status quo and prepares researchers for current and future challenges in establishment statistics and methods. Perfect for survey researchers, government statisticians, National Bank employees, economists, and undergraduate and graduate students in survey research and economics, Advances in Business Statistics, Methods and Data Collection will also earn a place in the toolkit of researchers working –with data– in industries across a variety of fields.
Author: Tiago Prince Sales
Publisher: Springer Nature
ISBN: 3031471121
Category : Computers
Languages : en
Pages : 353
Get Book Here
Book Description
This book constitutes the refereed proceedings of 7 workshops, held at the 42nd International Conference on Conceptual Modeling, ER 2023, held in Lisbon, Portugal, during November 6-9, 2023. The 28 full and 2 short papers were carefully reviewed and selected out of 53 submissions. Topics of interest span the entire spectrum of conceptual modeling, including research and practice in areas such as theories of concepts and ontologies, techniques for transforming conceptual models into effective implementations, and methods and tools for developing and communicating conceptual models. The following workshops are included in this volume: CMLS – 4th International Workshop on Conceptual Modeling for Life Sciences; CMOMM4FAIR – Third Workshop on Conceptual Modeling, Ontologies and (Meta)data Management for Findable, Accessible, Interoperable, and Reusable (FAIR) Data; EmpER – 6th International Workshop on Empirical Methods in Conceptual Modeling; JUSMOD – Second International Workshop on Digital Justice, Digital Law and Conceptual Modeling; OntoCom – 9th International Workshop on Ontologies and Conceptual Modeling; QUAMES – 4th International Workshop on Quality and Measurement of Model-Driven Software Development; SmartFood – First Workshop on Controlled Vocabularies and Data Platforms for Smart Food Systems.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309038812
Category : Medical
Languages : en
Pages : 340
Get Book Here
Book Description
It is not news that each of us grows old. What is relatively new, however, is that the average age of the American population is increasing. More and better information is required to assess, plan for, and meet the needs of a graying population. The Aging Population in the Twenty-First Century examines social, economic, and demographic changes among the aged, as well as many health-related topics: health promotion and disease prevention; quality of life; health care system financing and use; and the quality of careâ€"especially long-term care. Recommendations for increasing and improving the data availableâ€"as well as for ensuring timely access to themâ€"are also included.
Author: Peter Christen
Publisher: Springer Nature
ISBN: 3030597067
Category : Computers
Languages : en
Pages : 476
Get Book Here
Book Description
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: Li-Chun Zhang
Publisher: CRC Press
ISBN: 1351646729
Category : Mathematics
Languages : en
Pages : 246
Get Book Here
Book Description
The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons. Data integration involves combining data residing in different sources to enable statistical inference, or to generate new statistical data for purposes that cannot be served by each source on its own. This can yield significant gains for scientific as well as commercial investigations. However, valid analysis of such data should allow for the additional uncertainty due to entity ambiguity, whenever it is not possible to state with certainty that the integrated source is the target population of interest. Analysis of Integrated Data aims to provide a solid theoretical basis for this statistical analysis in three generic settings of entity ambiguity: statistical analysis of linked datasets that may contain linkage errors; datasets created by a data fusion process, where joint statistical information is simulated using the information in marginal data from non-overlapping sources; and estimation of target population size when target units are either partially or erroneously covered in each source. Covers a range of topics under an overarching perspective of data integration. Focuses on statistical uncertainty and inference issues arising from entity ambiguity. Features state of the art methods for analysis of integrated data. Identifies the important themes that will define future research and teaching in the statistical analysis of integrated data. Analysis of Integrated Data is aimed primarily at researchers and methodologists interested in statistical methods for data from multiple sources, with a focus on data analysts in the social sciences, and in the public and private sectors.
