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arXiv · 2006.01298

Identification Risks Evaluation of Partially Synthetic Data with the $\texttt{IdentificationRiskCalculation}$ R Package

Ryan Hornby·Jingchen Hu
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Abstract

We extend a general approach to evaluating identification risk of synthesized variables in partially synthetic data. For multiple continuous synthesized variables, we introduce the use of a radius $r$ in the construction of identification risk probability of each target record, and illustrate with working examples. We create the $\texttt{IdentificationRiskCalculation}$ R package to aid researchers and data disseminators in performing these identification risks evaluation calculations. We demonstrate our methods through the R package with applications to a data sample from the Consumer Expenditure Surveys, and discuss the impacts on risk and data utility of 1) the choice of radius $r$, 2) the choice of synthesized variables, and 3) the choice of number of synthetic datasets. We give recommendations for statistical agencies for synthesizing and evaluating identification risk of continuous variables.

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Ryan Hornby, Jingchen Hu. 2020-06-01. Identification Risks Evaluation of Partially Synthetic Data with the $\texttt{IdentificationRiskCalculation}$ R Package. https://arxiv.org/abs/2006.01298

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