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
中科院分区:
文献类型:
--
作者:
Cui, Yifan;Gong, Ruobin;Hannig, Jan;Hoffman, Kentaro
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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DOI:
--
发表时间:
2021
期刊:
影响因子:
--
作者:
Andrés F. Barrientos;Aaron R. Williams;C. Bowen;John Abowd;Jim Cilke;J. Debacker;Nada Eissa;Rick Evans;Dan Feenberg;Max Ghenis;Nick Hart;Matt Jensen;Barry Johnson;I. Lurie;Shelly Martinez;Robert Moffitt;Amy O’Hara;Jerry Reiter;Emmanuel Saez;Wade Shen;Aleksandra Slavković;Salil P. Vadhan;Lars Vilhuber IV Acknowledgments
通讯作者:
Lars Vilhuber IV Acknowledgments
DOI:
--
发表时间:
2018
期刊:
影响因子:
--
作者:
M. Freiman;Rolando A. Rodríguez;Jerome P. Reiter
通讯作者:
Jerome P. Reiter
DOI:
--
发表时间:
2022
期刊:
Harvard data science review
影响因子:
--
作者:
V. Hotz;Joseph Salvo
通讯作者:
Joseph Salvo
DOI:
--
发表时间:
2022
期刊:
Harvard data science review
影响因子:
--
作者:
Dan R. Boyd;Jayshree Sarathy
通讯作者:
Jayshree Sarathy
影响因子:
56.9
作者:
Ryan Steed;Terrance Liu;Zhiwei Steven Wu;A. Acquisti
通讯作者:
A. Acquisti