An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets

@article{Drechsler2011AnEE,
  title={An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets},
  author={J{\"o}rg Drechsler and Jerome P. Reiter},
  journal={Computational Statistics & Data Analysis},
  year={2011},
  volume={55},
  pages={3232-3243}
}
When intense redaction is needed to protect the confidentiality of data subjects’ identities and sensitive attributes, statistical agencies can use synthetic data approaches. To create synthetic data, the agency replaces identifying or sensitive values with draws from statistical models estimated from the confidential data. Many data producers are reluctant to implement this idea because (i) the quality of the generated data depends strongly on the quality of the underlying models, and (ii… CONTINUE READING
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