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Synthetic Datasets for Statistical Disclosure Control Theory and Implementation /
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 re...
| Call Number: | Libro Electrónico |
|---|---|
| Main Author: | |
| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | Inglés |
| Published: |
New York, NY :
Springer New York : Imprint: Springer,
2011.
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| Edition: | 1st ed. 2011. |
| Series: | Lecture Notes in Statistics,
201 |
| Subjects: | |
| Online Access: | Texto Completo |
Table of Contents:
- 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.