00000cmm a22000004a 4500 UP-99796217611212570 Buklod 20230215085534.0 m go j cr |n |||auu|a 110623s2011 xxu u | eng d 9781461403265 (eBook) (iLib)UPD-00215704374 DLC DML eng DMLUC HA 29 D74 2011eb Drechsler, Jorg Synthetic datasets for statistical disclosure control theory and implementation [electronic resource] by Jörg Drechsler. New York, NY Springer New York 2011. 1 online resource (xx, 138 p. ill.) Introduction -- Background on Multiply Imputed Synthetic Datasets -- Background on Multiple Imputation -- The IAB Establishment Panel -- Multiple Imputation for Nonresponse -- Fully Synthetic Datasets -- Partially Synthetic Datasets -- Multiple Imputation for Nonresponse and Statistical Disclosure Control -- A Two-Stage Imputation Procedure to Balance the Risk-Utility Trade-Off -- Chances and Obstacles for Multiply Imputed Synthetic Datasets. IP based subscription, on campus and remote access. Access via Electronic Resources of the UPD University Library Website. 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 developed so far, provides a brief history of synthetic datasets, and gives useful hints on how to deal with real data problems like nonresponse, skip patterns, or logical constraints. Each chapter is dedicated to one approach, first describing the general concept followed by a detailed application to a real dataset providing useful guidelines on how to implement the theory in practice. The discussed multiple imputation approaches include imputation for nonresponse, generating fully synthetic datasets, generating partially synthetic datasets, generating synthetic datasets when the original data is subject to nonresponse, and a two-stage imputation approach that helps to better address the omnipresent trade-off between analytical validity and the risk of disclosure. The book concludes with a glimpse into the future of synthetic datasets, discussing the potential benefits and possible obstacles of the approach and ways to address the concerns of data users and their understandable discomfort with using data that doesn?t consist only of the originally collected values. The book is intended for researchers and practitioners alike. It helps the researcher to find the state of the art in synthetic data summarized in one book with full reference to all relevant papers on the topic. But it is also useful for the practitioner at the statistical agency who is considering the synthetic data approach for data dissemination in the future and wants to get familiar with the topic. Electronic reproduction. New York SpringerLink 2011. Available via World Wide Web through SpringerLink. Social sciences Statistical methods. Multiple imputation (Statistics). Disclosure of information. Data protection. Electronic records Access control. Confidential communications. Statistics. Electronic books. Drechsler, Jorg. SpringerLink (Online service). Electronic Resource Available for University of the Philippines Diliman via SpringerLink. Click here to access http://link.springer.com/book/10.1007/978-1-4614-0326-5 FO Monograph UPD DMLR Electronic Resource