随机临床试验的顺序设计和分析:历史视角

IF 0.6 4区 数学 Q4 STATISTICS & PROBABILITY Sequential Analysis-Design Methods and Applications Pub Date : 2020-07-02 DOI:10.1080/07474946.2020.1823190
W. Rosenberger
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引用次数: 0

摘要

摘要瓦尔德发明的序列分析并没有针对临床试验;事实上,这项随机临床试验几乎是由大西洋彼岸的希尔同时发明的。Bross和Armitage在20世纪50年代初建立了与临床试验的联系,并在这十年中应用于多项试验。它在实践中的适用性受到限制,导致了一段干旱期,直到它用分组顺序方法死灰复燃。本文回顾了序列分析在实际随机临床试验中使用的历史背景。它不回顾方法论的发展,除非它们与历史和哲学背景有关。
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Sequential design and analysis in the randomized clinical trial: A historical perspective
Abstract Sequential analysis, as invented by Wald, was not targeted to clinical trials; in fact, the randomized clinical trial was being invented nearly simultaneously by Hill on the other side of the Atlantic. The connection to clinical trials was established by Bross and Armitage in the early 1950s and applied in a number of trials during that decade. Restrictions in its applicability in practice led to a dry spell until its resurgence with group sequential methods. This article reviews the historical context of the use of sequential analysis in actual randomized clinical trials. It does not review methodological developments, except as they relate to the historical and philosophical setting.
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来源期刊
CiteScore
1.40
自引率
12.50%
发文量
20
期刊介绍: The purpose of Sequential Analysis is to contribute to theoretical and applied aspects of sequential methodologies in all areas of statistical science. Published papers highlight the development of new and important sequential approaches. Interdisciplinary articles that emphasize the methodology of practical value to applied researchers and statistical consultants are highly encouraged. Papers that cover contemporary areas of applications including animal abundance, bioequivalence, communication science, computer simulations, data mining, directional data, disease mapping, environmental sampling, genome, imaging, microarrays, networking, parallel processing, pest management, sonar detection, spatial statistics, tracking, and engineering are deemed especially important. Of particular value are expository review articles that critically synthesize broad-based statistical issues. Papers on case-studies are also considered. All papers are refereed.
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