Evolution on the Generation and Analysis of Single Imputation Synthetic Datasets in Statistical Disclosure Control
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 …
Disclosure Control (SDC). Imputation is a widely used technique for generating privacy …
Evolution on the Generation and Analysis of Single Imputation Synthetic Datasets
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 …
data is automatically saved, and more and more, various organizations, businesses, and …
[图书][B] Synthetic datasets for statistical disclosure control: theory and implementation
J Drechsler - 2011 - books.google.com
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 …
to generating multiply imputed synthetic datasets. It describes all approaches that have been …
Background on Multiply Imputed Synthetic Datasets
J Drechsler, J Drechsler - … for Statistical Disclosure Control: Theory and …, 2011 - Springer
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 …
confidentiality. Two articles in this volume laid the foundation for the development of multiply …
Examining the robustness of fully synthetic data techniques for data with binary variables
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 …
concerns about the privacy of personal information. One proposed method for …
Generating multiply imputed synthetic datasets: theory and implementation
J Drechsler - 2010 - fis.uni-bamberg.de
The book describes different approaches to generating multiply imputed synthetic datasets
to guarantee confidentiality. Each chapter is dedicated to one approach, first describing the …
to guarantee confidentiality. Each chapter is dedicated to one approach, first describing the …
How can we analyze differentially-private synthetic datasets?
AS Charest - Journal of Privacy and Confidentiality, 2011 - journalprivacyconfidentiality.org
Synthetic datasets generated within the multiple imputation framework are now commonly
used by statistical agencies to protect the confidentiality of their respondents. More recently …
used by statistical agencies to protect the confidentiality of their respondents. More recently …
Multiple Imputation and Synthetic Data Generation with the R package NPBayesImputeCat
In many contexts, missing data and disclosure control are ubiquitous and challenging
issues. In particular at statistical agencies, the respondent-level data they collect from …
issues. In particular at statistical agencies, the respondent-level data they collect from …
Background on Multiple Imputation
J Drechsler, J Drechsler - … for Statistical Disclosure Control: Theory and …, 2011 - Springer
Multiple imputation, introduced by Rubin (1978) and discussed in detail in Rubin (1987;
2004), is an approach that retains the advantages of imputation while allowing the …
2004), is an approach that retains the advantages of imputation while allowing the …
[PDF][PDF] Multiple Imputation and Synthetic Data Generation with NPBayesImputeCat.
In many contexts, missing data and disclosure control are ubiquitous and challenging
issues. In particular, at statistical agencies, the respondent-level data they collect from …
issues. In particular, at statistical agencies, the respondent-level data they collect from …