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Synthetische Daten : Innovationspotential und gesellschaftliche Herausforderungen

, and . Impuls, Stiftung Neue Verantwortung, Berlin, (May 2018)

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Biases in multilevel analyses caused by cluster-specific fixed-effects imputation, , and . Behavior Research Methods, (August 2017)Secure Matrix Computation: A Viable Alternative to Record Linkage?, and . PSD, volume 12276 of Lecture Notes in Computer Science, page 240-254. Springer, (2020)Some Clarifications Regarding Fully Synthetic Data.. PSD, volume 11126 of Lecture Notes in Computer Science, page 109-121. Springer, (2018)Synthetische Daten : Innovationspotential und gesellschaftliche Herausforderungen, and . Impuls, Stiftung Neue Verantwortung, Berlin, (May 2018)Generating Useful Test Data for Complex Linked Employer-Employee Datasets., , and . Privacy in Statistical Databases, volume 7556 of Lecture Notes in Computer Science, page 165-178. Springer, (2012)Challenges in Measuring Utility for Fully Synthetic Data.. PSD, volume 13463 of Lecture Notes in Computer Science, page 220-233. Springer, (2022)Controlling Privacy Loss in Sampling Schemes: An Analysis of Stratified and Cluster Sampling., , , , and . FORC, volume 218 of LIPIcs, page 1:1-1:24. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2022)Non-parametric Differentially Private Confidence Intervals for the Median., , , , and . CoRR, (2021)Remote Data Access and the Risk of Disclosure from Linear Regression: An Empirical Study., , and . Privacy in Statistical Databases, volume 6344 of Lecture Notes in Computer Science, page 220-233. Springer, (2010)Accounting for Intruder Uncertainty Due to Sampling When Estimating Identification Disclosure Risks in Partially Synthetic Data., and . Privacy in Statistical Databases, volume 5262 of Lecture Notes in Computer Science, page 227-238. Springer, (2008)