Matthias Templ Bücher

Statistical Disclosure Control (SDC) zielt darauf ab, die erforderliche statistische Privatsphäre zu wahren, während Daten für Forscher zugänglich gemacht werden. Das Buch stellt das R-Paket sdcMicro vor, das eine effektive Wahrung der Vertraulichkeit von Mikrodaten ermöglicht, ohne die multivariate Datenstruktur zu verändern. Es erläutert die Konzepte und demonstriert die Anwendung anhand realer Daten. Zudem werden robuste Methoden zur Vermeidung von Informationsverlust durch Ausreißer und innovative Ansätze zur Imputation von fehlenden Werten, insbesondere bei kompositionalen Daten, behandelt.

Focusing on visualization and imputation techniques for missing values, this book provides practical applications using R. It covers various imputation methods, emphasizing visualization and data problem descriptions. The text delves into modern approaches, including robust imputation and deep learning, while outlining the advantages and disadvantages of each method. By clarifying the applicability of different techniques based on specific datasets, it serves as a comprehensive guide for practitioners seeking effective solutions to data challenges.

Explore the power of computational statistics and simulations in R to derive actionable insights from your data. This book offers practical techniques for analyzing complex datasets, emphasizing hands-on approaches and real-world applications. Readers will learn to implement various statistical methods and simulations, enhancing their analytical skills and decision-making capabilities. Perfect for data enthusiasts and professionals seeking to deepen their understanding of statistical analysis with R.

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.