多组等效测试

IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY Stat Pub Date : 2024-01-10 DOI:10.1002/sta4.645
Tony Pourmohamad, Herbert K. H. Lee
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引用次数: 0

摘要

等效测试而非差异测试是某些科学研究的重要组成部分。虽然现有文献的重点是比较两组的等效性,但实际应用中经常出现需要跨两组以上进行测试的情况。本文回顾了现有的多组测试方法,并提出了贝叶斯范式下的多组等效性测试新框架。与现有的几种替代方法相比,这种方法对等值边际的定义更具科学意义,测试功能也更强大。这种方法还可以根据未来差异对等效性进行新的定义。
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Equivalence testing for multiple groups
Testing for equivalence, rather than testing for a difference, is an important component of some scientific studies. While the focus of the existing literature is on comparing two groups for equivalence, real-world applications arise regularly that require testing across more than two groups. This paper reviews the existing approaches for testing across multiple groups and proposes a novel framework for multigroup equivalence testing under a Bayesian paradigm. This approach allows for a more scientifically meaningful definition of the equivalence margin and a more powerful test than the few existing alternatives. This approach also allows a new definition of equivalence based on future differences.
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来源期刊
Stat
Stat Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
1.10
自引率
0.00%
发文量
85
期刊介绍: Stat is an innovative electronic journal for the rapid publication of novel and topical research results, publishing compact articles of the highest quality in all areas of statistical endeavour. Its purpose is to provide a means of rapid sharing of important new theoretical, methodological and applied research. Stat is a joint venture between the International Statistical Institute and Wiley-Blackwell. Stat is characterised by: • Speed - a high-quality review process that aims to reach a decision within 20 days of submission. • Concision - a maximum article length of 10 pages of text, not including references. • Supporting materials - inclusion of electronic supporting materials including graphs, video, software, data and images. • Scope - addresses all areas of statistics and interdisciplinary areas. Stat is a scientific journal for the international community of statisticians and researchers and practitioners in allied quantitative disciplines.
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