A Bayesian Hierarchical Model Approach to Risk Estimation in Statistical Disclosure Limitation

A Bayesian Hierarchical Model Approach to Risk Estimation in Statistical Disclosure Limitation
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统计披露限制中风险估计的贝叶斯分层模型方法

DOI:
10.1007/978-3-540-25955-8_19
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发表时间:
2004
影响因子:
2.4
通讯作者:
J. Stander
J. Stander
中科院分区:
工程技术3区
文献类型:
--
作者:
S. Polettini;J. Stander

文献摘要

被引文献

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当用于研究的微数据文件发布时,外部用户可能会试图破坏机密性。出于这个原因,大多数国家统计机构采用某种形式的披露风险评估和数据保护。风险评估首先需要定义披露风险的度量。在本文中,我们以[BF98]的先前工作为基础,定义了一个用于风险估计的贝叶斯层次模型。我们采用了类似于[BKP90]和[Rin03]的超种群方法。对于每个关键变量值的组合,我们推导出给定观察到的样本频率的总体频率的后验分布。这种后验分布的知识使我们能够获得适当的总结,可用于估计披露的风险。一个这样的总结是总体频率或贝内代蒂-弗兰科尼风险的倒数的平均值,但我们也研究其他的,如模式。我们将我们的方法应用于意大利1991年人口普查数据的人工样本,该数据是通过广泛使用的抽样方案绘制的。我们报告这个应用程序的结果,并记录我们遇到的计算困难。我们获得的风险估计是合理的,但建议对我们的方法进行可能的改进和修改。我们将这些与潜在的替代策略一起讨论。
When microdata files for research are released, it is possible that external users may attempt to breach confidentiality. For this reason most National Statistical Institutes apply some form of disclosure risk assessment and data protection. Risk assessment first requires a measure of disclosure risk to be defined. In this paper we build on previous work by [BF98] to define a Bayesian hierarchical model for risk estimation. We follow a superpopulation approach similar to [BKP90] and [Rin03]. For each combination of values of the key variables we derive the posterior distribution of the population frequency given the observed sample frequency. Knowledge of this posterior distribution enables us to obtain suitable summaries that can be used to estimate the risk of disclosure. One such summary is the mean of the reciprocal of the population frequency or Benedetti-Franconi risk, but we also investigate others such as the mode. We apply our approach to an artificial sample of the Italian 1991 Census data, drawn by means of a widely used sampling scheme. We report on results of this application and document the computational difficulties that we encountered. The risk estimates that we obtain are sensible, but suggest possible improvements and modifications to our methodology. We discuss these together with potential alternative strategies.