减少反应适应试验中的风险患者 (PaR):数值研究

IF 1.7 Q3 MANAGEMENT IIMB Management Review Pub Date : 2023-12-01 DOI:10.1016/j.iimb.2023.09.002
L. Ramprasath, Mohammed Shahid Abdulla
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引用次数: 0

摘要

本文研究了在伦理最优反应自适应设计中,更高的统计能力与更高的优效治疗分配之间的二分法。尽管文献中的许多反应自适应设计都承诺更高的优效治疗分配率,但由于设计的多变性,这一点并不总能得到保证。为了解决这个问题,我们提出了一种以风险价值衡量标准为基础的新的反应自适应设计评估标准。我们还提供了在实际临床试验中应用该标准的示例。
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Reducing the patients-at-risk (PaR) in a response-adaptive trial: A numerical study

This article investigates the dichotomy between higher statistical power and higher allocation to better treatment in an ethical-optimal response-adaptive design. Although many response-adaptive designs in the literature promise higher allocation to the superior treatment, this is not always guaranteed due to the variability of the designs. A new criterion for evaluating response-adaptive designs, motivated by the value-at-risk measure, is proposed to address this problem. We also provide an illustration of applying this criterion in a real clinical trial.

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来源期刊
CiteScore
3.20
自引率
5.90%
发文量
31
审稿时长
68 days
期刊介绍: IIMB Management Review (IMR) is a quarterly journal brought out by the Indian Institute of Management Bangalore. Addressed to management practitioners, researchers and academics, IMR aims to engage rigorously with practices, concepts and ideas in the field of management, with an emphasis on providing managerial insights, in a reader friendly format. To this end IMR invites manuscripts that provide novel managerial insights in any of the core business functions. The manuscript should be rigorous, that is, the findings should be supported by either empirical data or a well-justified theoretical model, and well written. While these two requirements are necessary for acceptance, they do not guarantee acceptance. The sole criterion for publication is contribution to the extant management literature.Although all manuscripts are welcome, our special emphasis is on papers that focus on emerging economies throughout the world. Such papers may either improve our understanding of markets in such economies through novel analyses or build models by taking into account the special characteristics of such economies to provide guidance to managers.
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