Selected Topics of Statistical Disclosure Limitation PDF Download
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Author: Gregory J. Matthews
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Author: Gregory J. Matthews
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Author: Anco Hundepool
Publisher: John Wiley & Sons
ISBN: 1118348214
Category : Mathematics
Languages : en
Pages : 308
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Book Description
A reference to answer all your statistical confidentiality questions. This handbook provides technical guidance on statistical disclosure control and on how to approach the problem of balancing the need to provide users with statistical outputs and the need to protect the confidentiality of respondents. Statistical disclosure control is combined with other tools such as administrative, legal and IT in order to define a proper data dissemination strategy based on a risk management approach. The key concepts of statistical disclosure control are presented, along with the methodology and software that can be used to apply various methods of statistical disclosure control. Numerous examples and guidelines are also featured to illustrate the topics covered. Statistical Disclosure Control: Presents a combination of both theoretical and practical solutions Introduces all the key concepts and definitions involved with statistical disclosure control. Provides a high level overview of how to approach problems associated with confidentiality. Provides a broad-ranging review of the methods available to control disclosure. Explains the subtleties of group disclosure control. Features examples throughout the book along with case studies demonstrating how particular methods are used. Discusses microdata, magnitude and frequency tabular data, and remote access issues. Written by experts within leading National Statistical Institutes. Official statisticians, academics and market researchers who need to be informed and make decisions on disclosure limitation will benefit from this book.
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309047439
Category : Computers
Languages : en
Pages : 289
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Book Description
Americans are increasingly concerned about the privacy of personal dataâ€"yet we demand more and more information for public decision making. This volume explores the seeming conflicts between privacy and data access, an issue of concern to federal statistical agencies collecting the data, research organizations using the data, and individuals providing the data. A panel of experts offers principles and specific recommendations for managing data and improving the balance between needed government use of data and the privacy of respondents. The volume examines factors such as the growth of computer technology, that are making confidentiality an increasingly critical problem. The volume explores how data collectors communicate with data providers, with a focus on informed consent to use data, and describes the legal and ethical obligations data users have toward individual subjects as well as toward the agencies providing the data. In the context of historical practices in the United States, Canada, and Sweden, statistical techniques for protecting individuals' identities are evaluated in detail. Legislative and regulatory restraints on access to data are examined, including a discussion about their effects on research. This volume will be an important and thought-provoking guide for policymakers and agencies working with statistics as well as researchers and concerned individuals.
Author: United States. Federal Committee on Statistical Methodology. Subcommittee on Disclosure-Avoidance Techniques
Publisher:
ISBN:
Category : Government information
Languages : en
Pages : 84
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Author: Stephen E. Fienberg
Publisher:
ISBN:
Category :
Languages : en
Pages : 237
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Author: Leon Willenborg
Publisher: Springer Science & Business Media
ISBN: 146124028X
Category : Mathematics
Languages : en
Pages : 164
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Book Description
The aim of this book is to discuss various aspects associated with disseminating personal or business data collected in censuses or surveys or copied from administrative sources. The problem is to present the data in such a form that they are useful for statistical research and to provide sufficient protection for the individuals or businesses to whom the data refer. The major part of this book is concerned with how to define the disclosure problem and how to deal with it in practical circumstances.
Author: Matthias Templ
Publisher: Springer
ISBN: 3319502727
Category : Social Science
Languages : en
Pages : 299
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Book Description
This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods, disclosure risk, data utility, information loss and methods for simulating synthetic data. Introducing readers to the R packages sdcMicro and simPop, the book also features numerous examples and exercises with solutions, as well as case studies with real-world data, accompanied by the underlying R code to allow readers to reproduce all results. The demand for and volume of data from surveys, registers or other sources containing sensible information on persons or enterprises have increased significantly over the last several years. At the same time, privacy protection principles and regulations have imposed restrictions on the access and use of individual data. Proper and secure microdata dissemination calls for the application of statistical disclosure control methods to the da ta before release. This book is intended for practitioners at statistical agencies and other national and international organizations that deal with confidential data. It will also be interesting for researchers working in statistical disclosure control and the health sciences.
Author: Pat Doyle
Publisher: Elsevier Science & Technology
ISBN:
Category : Business & Economics
Languages : en
Pages : 474
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Book Description
There is a fundamental tension at the heart of every statistical agency mission. Each is charged with collecting high quality data to inform the national policy and enable statistical research. This necessitates dissemination of both summary and micro data. Each is also charged with protecting the confidentiality of survey respondents. This often necessitates the blurring of the data to reduce the probability of the re-identification of individuals. The tradeoff dilemma, which could well be stated as protecting confidentiality (avoiding disclosure) but optimizing access, has become more complex as both technological advances and public perceptions have altered in an information age. Fortunately, statistical disclosure techniques have kept pace with these changes. This volume is intended to provide a review of new state of the art techniques that directly address these issues from both a theoretical and practical perspective. It provides a review of new research in the area of confidentiality and statistical disclosure techniques. A major section of the book provides an overview of new advances in the field of both economic and demographic data in measuring disclosure risk and information loss. It also presents new information on the different approaches taken by statistical agencies in disseminating data - ranging from licensing agreements , to secure access and provides a new survey of what statistical disclosure techniques are used by statistical agencies around the world. This is complimented by a series of chapters on public perceptions of statistical agency actions, including the results of a new survey on business perceptions. The book concludes with a chapter on the challenges of technology to data protection. National Statistical Agencies, statistical practitioners, thinktanks, research organisations and universities will find this a useful tool.
Author: Jörg Drechsler
Publisher: Springer Science & Business Media
ISBN: 146140326X
Category : Social Science
Languages : en
Pages : 148
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Book Description
The aim of this book is to give the reader a detailed introduction to the different approaches to generating multiply imputed synthetic datasets. It describes all approaches that have been developed so far, provides a brief history of synthetic datasets, and gives useful hints on how to deal with real data problems like nonresponse, skip patterns, or logical constraints. Each chapter is dedicated to one approach, first describing the general concept followed by a detailed application to a real dataset providing useful guidelines on how to implement the theory in practice. The discussed multiple imputation approaches include imputation for nonresponse, generating fully synthetic datasets, generating partially synthetic datasets, generating synthetic datasets when the original data is subject to nonresponse, and a two-stage imputation approach that helps to better address the omnipresent trade-off between analytical validity and the risk of disclosure. The book concludes with a glimpse into the future of synthetic datasets, discussing the potential benefits and possible obstacles of the approach and ways to address the concerns of data users and their understandable discomfort with using data that doesn’t consist only of the originally collected values. The book is intended for researchers and practitioners alike. It helps the researcher to find the state of the art in synthetic data summarized in one book with full reference to all relevant papers on the topic. But it is also useful for the practitioner at the statistical agency who is considering the synthetic data approach for data dissemination in the future and wants to get familiar with the topic.
Author: United States. Federal Committee on Statistical Methodology. Subcommittee on Disclosure Limitation Methodology
Publisher:
ISBN:
Category : Confidential communications
Languages : en
Pages : 131
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Book Description
