关于 Ethan M. Alt、Xiuya Chang、Xun Jiang、Qing Liu、May Mo、H. Amy Xia 和 Joseph G. Ibrahim 所著《LEAP:从历史数据中借用信息的潜在可交换性先验》的讨论。

IF 1.4 4区 数学 Q3 BIOLOGY
Biometrics Pub Date : 2024-07-01 DOI:10.1093/biomtc/ujae085
Darren Scott, Alex Lewin
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引用次数: 0

摘要

在下面的讨论中,我们将介绍在贝叶斯借用和相关模型中对可交换性所做的各种假设。在此背景下,我们能够强调在历史数据中的个体与当前数据可交换的假设下动态贝叶斯借用的困难,从而突出潜在可交换性先验的优势和新特点。由于借用方法在临床试验中常用于增强对照组,因此我们发现了在这种情况下应用该方法可能面临的一些挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Discussion on "LEAP: the latent exchangeability prior for borrowing information from historical data" by Ethan M. Alt, Xiuya Chang, Xun Jiang, Qing Liu, May Mo, H. Amy Xia, and Joseph G. Ibrahim.

In the following discussion, we describe the various assumptions of exchangeability that have been made in the context of Bayesian borrowing and related models. In this context, we are able to highlight the difficulty of dynamic Bayesian borrowing under the assumption of individuals in the historical data being exchangeable with the current data and thus the strengths and novel features of the latent exchangeability prior. As borrowing methods are popular within clinical trials to augment the control arm, some potential challenges are identified with the application of the approach in this setting.

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来源期刊
Biometrics
Biometrics 生物-生物学
CiteScore
2.70
自引率
5.30%
发文量
178
审稿时长
4-8 weeks
期刊介绍: The International Biometric Society is an international society promoting the development and application of statistical and mathematical theory and methods in the biosciences, including agriculture, biomedical science and public health, ecology, environmental sciences, forestry, and allied disciplines. The Society welcomes as members statisticians, mathematicians, biological scientists, and others devoted to interdisciplinary efforts in advancing the collection and interpretation of information in the biosciences. The Society sponsors the biennial International Biometric Conference, held in sites throughout the world; through its National Groups and Regions, it also Society sponsors regional and local meetings.
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