Suggested CitationAbowd, John M., Ian M. Schmutte and Lars Vilhuber (2021). "Disclosure Limitation and Confidentiality Protection in Linked Data."in Administrative Records for Survey Methodology (eds A.Y. Chun, M.D. Larsen, G. Durrant and J.P. Reiter).
This chapter provides an overview of the methods that have been developed and implemented to safeguard privacy, while providing researchers the means to draw valid conclusions from protected data. It focuses on the protections that pertain to the linked nature of the data. The protection mechanisms are both physical and statistical, but exist because of the need to balance the privacy of the respondents, including the confidentiality protection their data receive, with society’s need and desire for ever more detailed, timely, and accurate statistics. To illustrate the application of new disclosure avoidance techniques, the chapter describes three examples of linked data and the means by which confidentiality protection is applied to each. Health and Retirement Study–Social Security Administration (SSA) data, Survey of Income and Program Participation–SSA–Internal Revenue Service, inked Establishment and Employee Records Several methods are currently used by national statistical offices and other data collecting agencies to provide access to confidential data.