Statistical Disclosure Control for Microdata : Methods and Applications in R / by Matthias Templ.

Format:

Book

Author/Creator:

Templ, Matthias, Author.

Language:

English

Subjects (All):

Social sciences--Statistical methods.

Social sciences.

Mathematical statistics--Data processing.

Mathematical statistics.

Statistics.

Biometry.

Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.

Statistics and Computing.

Statistical Theory and Methods.

Statistics in Business, Management, Economics, Finance, Insurance.

Biostatistics.

Local Subjects:

Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.

Statistics and Computing.

Statistical Theory and Methods.

Statistics in Business, Management, Economics, Finance, Insurance.

Biostatistics.

Physical Description:

1 online resource (XIX, 287 p. 37 illus., 27 illus. in color.)

Edition:

1st ed. 2017.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2017.

Summary:

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 dat a 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.

Contents:

Preface

Software

Basic Concepts

Disclosure Risk

Methods for Data Perturbation

Data Utility and Information Loss

Synthetic Data

Practical Guidelines

Case Studies

Solutions

Index.

Notes:

Includes bibliographical references and index.

ISBN:

3-319-50272-7