Post randomisation for statistical disclosure control: Theory and implementation
Post randomisation for statistical disclosure control: Theory and implementation
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统计披露控制的随机化后：理论与实施
DOI：
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发表时间：
1997
期刊：
影响因子：
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通讯作者：
P. P. De
中科院分区：
文献类型：
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作者：
J. Gouweleeuw;P. Kooiman;L. Willenborg;P. P. De
本文介绍了随机化后方法 (PRAM) 作为微数据文件中分类变量的披露保护方法。应用 PRAM 意味着对于微数据文件中的每条记录，一个或多个分类变量的分数根据预定的概率机制发生变化（独立于其他记录）。由于原始数据文件受到干扰，入侵者将很难识别与群体中某些个体相对应的记录。原始文件中的记录因此受到保护，这是应用 PRAM 的主要目标。另一方面，由于应用 PRAM 时使用的概率机制是已知的，因此可以从扰动的数据文件中估计（潜在）真实数据的特征。因此，应用PRAM后仍然可以进行各种统计分析。最初，我们开发 PRAM 作为连续变量加噪声的分类变量模拟；参见 Fuller (1993)、Hwang (1986) 以及 Kim 和 Winkler (1995)。只有在我们发展了大部分理论之后，我们才意识到我们的方法与调查抽样中应用的随机响应技术之间的明显关系；参见 Warner (1965, 1971) 以及 Chaudhuri 和 Mukerjee (1988)。此方法适用于受访者不太可能在面对面环境中如实回答的高度敏感问题。通过将问题嵌入到随机化后方法 (PRAM) 中，是一种用于分类变量披露保护的微扰方法。应用 PRAM 意味着对于微数据文件中的每条记录，许多变量的分数根据指定的概率机制发生变化。本文考虑了 PRAM 对数据安全性和数据统计质量的影响。在实践中应用 PRAM 时，必须做出许多决定，例如应用哪些变量以及以何种方式应用 PRAM。本文将简要讨论这些问题。例如，荷兰统计局针对使用 PRAM 保护荷兰国家旅行调查的可能性进行了调查。
This article introduces the Post RAndomisation Method (PRAM) as a method for disclosure protection of the categorical variables in a microdata ®le. Applying PRAM means that for each record in a microdata ®le the score on one or more categorical variables is changed (independently of the other records) according to a predetermined probability mechanism. Since the original data ®le is perturbed, it will be dif®cult for an intruder to identify records as corresponding to certain individuals in the population. The records in the original ®le are thus protected, which is the main goal of applying PRAM. On the other hand, since the probability mechanism that is used when applying PRAM is known, characteristics of the (latent) true data can be estimated from the perturbed data ®le. Hence it is still possible to perform all kinds of statistical analyses after PRAM has been applied. Originally we developed PRAM as the categorical variable analogon of noise addition to continuous variables; see e.g., Fuller (1993), Hwang (1986), and Kim and Winkler (1995). Only after we had developed most of the theory did we become aware of the obvious relationship of our method with the randomised response technique applied in survey sampling; see e.g., Warner (1965, 1971) and Chaudhuri and Mukerjee (1988). This method is employed in the case of highly sensitive questions to which the respondent is not likely to respond truthfully in a face-to-face setting. By embedding the question in The Post RAndomisation Method (PRAM) is a perturbative method for disclosure protection of categorical variables. Applying PRAM means that for each record in a microdata ®le the score on a number of variables is changed according to a speci®ed probability mechanism. This article considers the effect of PRAM on both the safety of the data and the statistical quality of the data. When applying PRAM in practice, a number of decisions have to be made, as for example to which variables and in what way to apply PRAM. These issues are brie ̄y discussed in this article. As an example, the result of an investigation performed at Statistics Netherlands into the possibility of protecting the Dutch National Travel Survey using PRAM is presented.