Journal of the Royal Statistical Society Series A (Statistics in Society) · 2004 · 236 citations · 10 references
ComputingData ScienceDemographyData EthicsData ManagementPrivacy EngineeringData AnalysisData AnonymizationData ProtectionMissing Data HandlingMissing Data ImputationMissing Data MethodsData ImputationData TransparencyData ValidityEmpirical EvaluationGovernment Data ReleaseMicrodata AnonymizationPrivacy PreservationUtility-privacy Tradeoff
Summary The paper presents an illustration and empirical study of releasing multiply imputed, fully synthetic public use microdata. Simulations based on data from the US Current Population Survey are used to evaluate the potential validity of inferences based on fully synthetic data for a variety of descriptive and analytic estimands, to assess the degree of protection of confidentiality that is afforded by fully synthetic data and to illustrate the specification of synthetic data imputation models. Benefits and limitations of releasing fully synthetic data sets are discussed.
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