威尔科克森等级总和试验用于检测组序列临床试验中的单边混合替代品
Dylan C Friel1, Daniel R Jeske1
1Department of Statistics, University of California, Riverside, CA, USA.
Statistical methods in medical research
|July 11, 2023
概括
这项研究引入了使用威尔科克森等级和统计学来检测混合物分布中的治疗效应的新型组序列测试,即使在错误指定的参数中,也提供了强大的I型错误控制.
科学领域:
- 生物统计学 生物统计学
- 临床试验设计 临床试验设计
- 统计推理 统计推理
背景情况:
- 传统的临床试验方法假设治疗效应是一个简单的转变,这可能不适用于所有人.
- 对治疗无反应需要使用混合物分布来建模治疗组的变异性.
- 现有的统计方法在捕捉复杂的治疗效应分布方面可能缺乏灵活性.
研究的目的:
- 开发和评估用于检测单面混合物替代品的组序测试程序.
- 评估基于Wilcoxon排列和统计数据的测试性能,在组序列设计中.
- 提供在混合物分布设置中确定临界值和样本大小的方法.
主要方法:
- 在一个群组顺序框架内使用了Wilcoxon排列和统计.
- 使用错误支出函数来顺序分配I型和II型错误率.
- 针对拟议的测试统计数据,研究了非对称的多变量正常性.
- 评估时刻的方法和受约束的方法对治疗效果的估计.
主要成果:
- 为混合物分配替代方案开发了两组顺序测试程序.
- 对于两个拟议的测试统计数据,确定了非对称的多变量正常性.
- 开发的测试证明了在保持I型错误率的稳定性,即使有错误指定的参数.
- 两种测试程序被发现是不对称的.
结论:
- 拟议的组序列试验有效地处理混合物分布,适应对治疗的不反应.
- 这些方法提供可靠的I型错误控制,并且在异构上相当.
- 该研究为评估临床试验中治疗效果提供了更一般的框架.
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