Beschreibung:
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.
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.