Health Services Research & Development, VA Puget Sound Health Care System, Seattle, WA, 98108, USA.
International Center for Mathematical Research, Peking University, Beijing, 100871, China.
Stat Med. 2018 Nov 10;37(25):3693-3706. doi: 10.1002/sim.7667. Epub 2018 Jun 21.
Statistical agencies are releasing statistical data to other agencies for research purposes or to inform public policy. Prior to data release, these agencies have a legal and ethical obligation to protect the confidentiality of individuals in the data. Agencies often release altered versions of the data, but there usually remains risks of disclosure. Many well-studied risk measures are available to assess risk; however, many agencies today continue to use subjective judgement, past experience, and ad hoc rules or checklists to assess disclosure risk. More recently, there has been a recognized demand for quantitative risk measures that provide a more objective criteria for data release. This tutorial provides an overview of the statistical disclosure control framework for microdata. We focus on the risk analysis stage within this framework by defining existing disclosure risk measures and how to estimate them with available software.
统计机构将统计数据发布给其他机构用于研究目的或为公共政策提供信息。在数据发布之前，这些机构有法律和道德义务保护数据中个人的机密性。机构通常会发布数据的修改版本，但仍然存在数据泄露的风险。有许多经过充分研究的风险度量标准可用于评估风险；然而，如今许多机构仍继续使用主观判断、以往经验以及特别规则或清单来评估披露风险。最近，人们越来越需要定量风险度量标准，以便为数据发布提供更客观的标准。本教程概述了微观数据的统计披露控制框架。我们通过定义现有的披露风险度量标准以及如何使用可用软件对其进行估计，重点介绍了该框架中的风险分析阶段。
