4 papers
It does what it says on the tin: safe synthetic data from coarsened margins
Gillian M Raab
This paper proposes a method of creating synthetic data (SD) that will have two important advantages for the user compared to other methods currently available. The first is transp…
Four checks for low-fidelity synthetic data: recommendations for disclosure control and quality evaluation
Gillian M Raab, Sophie McCall, Liam Cavin
Confidential administrative data is usually only available to researchers within a trusted research environment (TRE). Recently, some UK groups have proposed that low-fidelity synt…
Privacy risk from synthetic data: practical proposals
Gillian M Raab
This paper proposes and compares measures of identity and attribute disclosure risk for synthetic data. Data custodians can use the methods proposed here to inform the decision as…
Practical privacy metrics for synthetic data
Gillian M Raab, Beata Nowok, Chris Dibben
This paper explains how the synthpop package for R has been extended to include functions to calculate measures of identity and attribute disclosure risk for synthetic data that me…