Practical Applications in Statistical Disclosure Control Using R

This chapter gives a practitioner-oriented account of applying statistical disclosure control to real microdata using R. It walks through the practical decisions an analyst faces — identifying key variables, estimating risk, choosing among recoding, suppression, and perturbation methods, and checking the resulting data utility — and shows how to carry them out reproducibly. The emphasis is on bridging methodological theory and the realities of working with confidential datasets. Appearing in a Springer volume on privacy and anonymity in information management systems, it is an applied complement to the more methodological SDC literature.