Statistical disclosure control for microdata. Methods and applications in R. (English) Zbl 1437.62006

Cham: Springer (ISBN 978-3-319-50270-0/hbk; 978-3-319-84362-9/pbk; 978-3-319-50272-4/ebook). xix, 287 p. (2017).
Publisher’s 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.


62-02 Research exposition (monographs, survey articles) pertaining to statistics
68P27 Privacy of data
62D05 Sampling theory, sample surveys
62D20 Causal inference from observational studies
62B10 Statistical aspects of information-theoretic topics
62-08 Computational methods for problems pertaining to statistics
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