Adding noise; Data perturbation; Recodings; Sampling; Synthetic data
Matrix Masking refers to a class of statistical disclosure limitation (SDL) methods used to protect confidentiality of statistical data, transforming an n × p (cases by variables) data matrix Z through pre- and post-multiplication and the possible addition of noise.
- 1.Doyle P, Lane JI, Theeuwes JJM, Zayatz L, editors. Confidentiality, disclosure and data access: theory and practical application for statistical agencies. New York: Elsevier; 2001.Google Scholar
- 2.Duncan GT, Jabine TB, De Wolf VA, editors. Private lives and public policies. Report of the Committee on National Statistics’ panel on confidentiality and data access. Washington, DC: National Academy Press; 1993.Google Scholar
- 4.Federal Committee on Statistical Methodology. Report on statistical disclosure limitation methodology, Statistical policy working paper 22. Washington, DC: U.S. Office of Management and Budget; 1994.Google Scholar