Technical Comment on “Policy impacts of statistical uncertainty and privacy”

Technical Comment on “Policy impacts of statistical uncertainty and privacy”
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关于“统计不确定性和隐私的政策影响”的技术评论

DOI:
10.1126/science.adf9724
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发表时间:
2023
期刊:
影响因子:
56.9
通讯作者:
Hoffman, Kentaro
Hoffman, Kentaro
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Cui, Yifan;Gong, Ruobin;Hannig, Jan;Hoffman, Kentaro

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斯蒂德特等人。 说明官方统计数据产品的质量可能对其所依据的政策决策的准确性、稳定性和公平性产生至关重要的影响。作者提醒我们,无论数据如何负责任地整理,都可能出错。通过这一评论,我们强调对官方统计数据产品进行原则性质量评估的重要性。我们观察到 Steedet 等人采用的质量评估程序。需要改进,因为(i)所使用的估计器的不可接受性,以及(ii)它在估计器和观测数据的联合空间上得出的不一致的概率模型。我们讨论了替代统计方法的设计,以对官方统计数据产品进行原则性的质量评估,展示了两种基于模拟的方法,通过多级经验贝叶斯模型进行可接受的极小最大收缩估计。为了使政策制定者和利益相关者准确评估数据在特定背景下的可用性,评估应考虑数据固有的不确定性来源和下游用例,例如基于这些数据产品的政策决策。
Steedet al. illustrates the crucial impact that the quality of official statistical data products may exert on the accuracy, stability, and equity of policy decisions on which they are based. The authors remind us that data, however responsibly curated, can be fallible. With this comment, we underscore the importance of conducting principled quality assessment of official statistical data products. We observe that the quality assessment procedure employed by Steedet al. needs improvement, due to (i) the inadmissibility of the estimator used, and (ii) the inconsistent probability model it induces on the joint space of the estimator and the observed data. We discuss the design of alternative statistical methods to conduct principled quality assessments for official statistical data products, showcasing two simulation-based methods for admissible minimax shrinkage estimation via multilevel empirical Bayesian modeling. For policymakers and stakeholders to accurately gauge the context-specific usability of data, the assessment should take into account both uncertainty sources inherent to the data and the downstream use cases, such as policy decisions based on those data products.
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