Abstract Contingency tables provide a convenient format to publish summary data from confidential survey and administrative records that capture a wide range of social and economic information. By their nature, contingency tables enable aggregation of potentially sensitive data, limiting disclosure of identifying information. Furthermore, censoring or perturbation can be used to desensitise low cell counts when they arise. However, access to detailed cross-classified tables for research is often restricted by data custodians when too many censored or perturbed cells are required to preserve privacy. In this article, we describe a framework for selecting and combining log-linear models when accessible data is restricted to overlapping marginal contingency tables. The approach is demonstrated through application to housing transition data from the Australian Census Longitudinal Data set provided by the Australian Bureau of Statistics.

中文翻译：

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分析动态生成的重叠列联表中的敏感数据

摘要列联表提供了一种方便的格式，可以发布机密调查和行政记录中的摘要数据，这些摘要捕获了广泛的社会和经济信息。根据其性质，列联表可以汇总潜在的敏感数据，从而限制了标识信息的公开。此外，检查或扰动可用于使低细胞数出现时降低灵敏度。但是，当需要太多检查或扰动的单元来保护隐私时，数据保管人通常会限制访问详细的交叉分类表进行研究。在本文中，我们描述了一个框架，用于在可访问数据限于重叠的边际偶发表时选择和组合对数线性模型。