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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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Springer New York : Imprint: Springer,
2011.
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| Edición: | 1st ed. 2011. |
| Colección: | Lecture Notes in Statistics,
201 |
| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- 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.