Abstract
In 1993, Rubin suggested creating fully synthetic datasets based on the multipleimputation framework. His idea was to treat all units in the population that have not been selected in the sample as missing data, impute them according to the multipleimputation approach, and draw simple random samples from these imputed populations for release to the public. Most surveys are conducted using complex sampling designs. Releasing simple random samples simplifies research for the potential user of the data since the design doesn’t have to be incorporated in the model. It is not necessary, however, to release simple random samples.
Most of this chapter is taken from Drechsler et al. (2008b) and Drechsler and Reiter (2009).
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© 2011 Springer Science+Business Media, LLC
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Drechsler, J. (2011). Fully Synthetic Datasets. In: Synthetic Datasets for Statistical Disclosure Control. Lecture Notes in Statistics(), vol 201. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0326-5_6
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DOI: https://doi.org/10.1007/978-1-4614-0326-5_6
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