There is a significant public demand for rapid data-driven scientific investigations using
aggregated sensitive information. However, many technical challenges and regulatory …

In data integration contexts, two statistical agencies seek to merge their separate databases
into one file. The agencies also may seek to disseminate data to the public based on the …

We present an overview of the evolution of single imputation synthetic datasets in Statistical
Disclosure Control (SDC). Imputation is a widely used technique for generating privacy …

In today's world, simply using a smartphone leads to the creation of a vast array of data. This
data is automatically saved, and more and more, various organizations, businesses, and …

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 …

Abstract In 1993, the Journal of Official Statistics published a special issue on data
confidentiality. Two articles in this volume laid the foundation for the development of multiply …

Objectives. To develop an imputation method to produce estimates for suppressed values
within a shared government administrative data set to facilitate accurate data sharing and …

In order to understand the methods for generating synthetic data, it is important to start with
an understanding of the basis from which these methods have arisen. Viewed purely from …

There is a growing demand for public use data while at the same time there are increasing
concerns about the privacy of personal information. One proposed method for …

The book describes different approaches to generating multiply imputed synthetic datasets
to guarantee confidentiality. Each chapter is dedicated to one approach, first describing the …