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Statistical Disclosure Control.
A reference to answer all your statistical confidentiality questions. This handbook provides technical guidance on statistical disclosure control and on how to approach the problem of balancing the need to provide users with statistical outputs and the need to protect the confidentiality of responde...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , , , , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken :
John Wiley & Sons,
2012.
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| Colección: | Wiley series in survey methodology.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Statistical Disclosure Control; Contents; Preface; Acknowledgements; 1 Introduction; 1.1 Concepts and definitions; 1.1.1 Disclosure; 1.1.2 Statistical disclosure control; 1.1.3 Tabular data; 1.1.4 Microdata; 1.1.5 Risk and utility; 1.2 An approach to Statistical Disclosure Control; 1.2.1 Why is confidentiality protection needed?; 1.2.2 What are the key characteristics and uses of the data?; 1.2.3 What disclosure risks need to be protected against?; 1.2.4 Disclosure control methods; 1.2.5 Implementation; 1.3 The chapters of the handbook.
- 2 Ethics, principles, guidelines and regulations
- a general background; 2.1 Introduction; 2.2 Ethical codes and the new ISI code; 2.2.1 ISI Declaration on Professional Ethics; 2.2.2 New ISI Declaration on Professional Ethics; 2.2.3 European Statistics Code of Practice; 2.3 UNECE principles and guidelines; 2.3.1 UNECE Principles and Guidelines on Confidentiality Aspects of Data Integration; 2.3.2 Future activities on the UNECE principles and guidelines; 2.4 Laws; 2.4.1 Committee on Statistical Confidentiality; 2.4.2 European Statistical System Committee; 3 Microdata; 3.1 Introduction.
- 3.2 Microdata concepts; 3.2.1 Stage 1: Assess need for confidentiality protection; 3.2.2 Stage 2: Key characteristics and use of microdata; 3.2.3 Stage 3: Disclosure risk; 3.2.4 Stage 4: Disclosure control methods; 3.2.5 Stage 5: Implementation; 3.3 Definitions of disclosure; 3.3.1 Definitions of disclosure scenarios; 3.4 Definitions of disclosure risk; 3.4.1 Disclosure risk for categorical quasi-identifiers; 3.4.2 Notation and assumptions; 3.4.3 Disclosure risk for continuous quasi-identifiers; 3.5 Estimating re-identification risk; 3.5.1 Individual risk based on the sample: Threshold rule.
- 3.5.2 Estimating individual risk using sampling weights; 3.5.3 Estimating individual risk by Poisson model; 3.5.4 Further models that borrow information from other sources; 3.5.5 Estimating per record risk via heuristics; 3.5.6 Assessing risk via record linkage; 3.6 Non-perturbative microdata masking; 3.6.1 Sampling; 3.6.2 Global recoding; 3.6.3 Top and bottom coding; 3.6.4 Local suppression; 3.7 Perturbative microdata masking; 3.7.1 Additive noise masking; 3.7.2 Multiplicative noise masking; 3.7.3 Microaggregation; 3.7.4 Data swapping and rank swapping; 3.7.5 Data shuffling; 3.7.6 Rounding.
- 3.7.7 Re-sampling; 3.7.8 PRAM; 3.7.9 MASSC; 3.8 Synthetic and hybrid data; 3.8.1 Fully synthetic data; 3.8.2 Partially synthetic data; 3.8.3 Hybrid data; 3.8.4 Pros and cons of synthetic and hybrid data; 3.9 Information loss in microdata; 3.9.1 Information loss measures for continuous data; 3.9.2 Information loss measures for categorical data; 3.10 Release of multiple files from the same microdata set; 3.11 Software; 3.11.1 æ-argus; 3.11.2 sdcMicro; 3.11.3 IVEware; 3.12 Case studies; 3.12.1 Microdata files at Statistics Netherlands.
- 3.12.2 The European Labour Force Survey microdata for research purposes.