Name
Title | ||
|---|---|---|
Adjusting survey weights when altering identifying design variables via synthetic data |
Abstract | ||
|---|---|---|
Statistical agencies alter values of identifiers to protect respondents' confidentiality. When these identifiers are survey design variables, leaving the original survey weights on the file can be a disclosure risk. Additionally, the original weights may not correspond to the altered values, which impacts the quality of design-based (weighted) inferences. In this paper, we discuss some strategies for altering survey weights when altering design variables. We do so in the context of simulating identifiers from probability distributions, i.e. partially synthetic data. Using simulation studies, we illustrate aspects of the quality of inferences based on the different strategies. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11930242_16 | Privacy in Statistical Databases |
Keywords | Field | DocType |
adjusting survey weight,design variable,simulating identifiers,original survey weight,disclosure risk,different strategy,survey design variable,statistical agency,survey weight,original weight,synthetic data,altered value,probability distribution,survey design,multiple imputation | Data mining,Confidentiality,Identifier,Inference,Computer science,Synthetic data,Survey research,Probability distribution,Imputation (statistics),Information privacy,Statistics | Conference |
Volume | ISSN | ISBN |
4302 | 0302-9743 | 3-540-49330-1 |
Citations | PageRank | References |
8 | 1.39 | 1 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robin Mitra | 1 | 28 | 3.26 |
| Jerome P. Reiter | 2 | 216 | 22.12 |