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...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Livre numérique |
| Sprache: | Anglais |
| Veröffentlicht: |
New York, NY :
Springer New York
2011.
Cham : Springer Nature |
| Schriftenreihe: | Lecture Notes in Statistics
201 |
| Schlagworte: | |
| Online Zugang: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Anmerkung: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Synthetic datasets for statistical disclosure control, theory and implementation, Jörg Drechsler, New York, Springer, 2011, 1 vol. (XX-138 p.), Lecture notes in statistics, 978-1-461-40325-8 • Synthetic Datasets for Statistical Disclosure Control, Texte imprimé, 9781461403272 |
| LEADER | 04302nam a22003857a 4500 | ||
|---|---|---|---|
| 001 | 968909 | ||
| 008 | 110722s2011 xx ||| |||| 00| 0 eng d | ||
| 009 | PPN153869275 | ||
| 020 | |a 9781461403265 | ||
| 020 | |a 9781461403265 | ||
| 041 | 0 | |a eng | |
| 082 | |a 519.5 | ||
| 084 | |a 62-07. 2010 | ||
| 084 | |a 62D05. 2010 | ||
| 100 | 1 | |a Drechsler, Jörg. | |
| 245 | 1 | 0 | |a Synthetic datasets for statistical disclosure control : |b theory and implementation |c Jörg Drechsler. |
| 260 | |a New York, NY : |b Springer New York. | ||
| 260 | |a Cham : |b Springer Nature, |c 2011. | ||
| 490 | 0 | |a Lecture Notes in Statistics |v 201 |x 2197-7186 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 0 | |a 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. | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. chttps://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a 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. | ||
| 650 | |a Statistique | ||
| 650 | |a Échantillonnage (statistique) | ||
| 776 | 0 | |0 154806021 |t Synthetic datasets for statistical disclosure control |o theory and implementation |f Jörg Drechsler |c New York |n Springer |d 2011 |p 1 vol. (XX-138 p.) |s Lecture notes in statistics |z 978-1-461-40325-8 | |
| 776 | 0 | |t Synthetic Datasets for Statistical Disclosure Control |b Texte imprimé |z 9781461403272 | |
| 856 | 4 | |q PDF |u https://doi.org/10.1007/978-1-4614-0326-5 |z Accès sur la plateforme de l'éditeur | |
| 856 | 4 | |u https://revue-sommaire.istex.fr/ark:/67375/8Q1-958GN2GC-3 |z Accès sur la plateforme Istex | |
| 856 | 4 | |5 452349901:75061515X |u https://ezproxy.univ-orleans.fr/login?url=https://doi.org/10.1007/978-1-4614-0326-5 |z Accès Université d'Orléans | |
| 856 | 4 | |5 180339901:753973723 |u https://ezproxy.insa-cvl.fr/login?qurl=https://doi.org/10.1007/978-1-4614-0326-5 |z Accès INSA CVL | |
| 997 | |0 968909 |1 Livre numérique |a Ressource numérique |b INSA |b ENSA |c 0/Bibliothèque numérique/ |c 1/Bibliothèque numérique/Autre ressource numérique/ | ||