临床试验中不成比例危险的方法:系统性审查
Maximilian Bardo1,2, Cynthia Huber1,2, Norbert Benda1,3
1Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany.
Statistical methods in medical research
|April 9, 2024
概括
时间到事件数据分析的统计方法通常依赖于比例危险假设. 本综述确定并综合了不成比例危险的方法,为研究人员在这个复杂的领域进行导航提供了指导.
科学领域:
- 生物统计学 生物统计学
- 生存分析的分析.
- 统计学方法论 统计学方法论
背景情况:
- 常见的时间到事件分析方法,如日志等级测试和考克斯模型,假设相对的危险.
- 这种假设在现实数据中经常受到挑战.
- 现有的不成比例危险的方法缺乏关于最佳实践的明确共识.
研究的目的:
- 系统地识别和审查统计方法和软件来分析具有不成比例危险的时间到事件数据.
- 提供关于可用的方法的统一概述和指导.
主要方法:
- 对非比例危险的统计方法进行系统的文献搜索.
- 从907个已识别的摘要中包含了211篇方法论文章.
- 统一符号用于呈现不同的统计方法.
主要成果:
- 确定了广泛的方法,包括效果测量,估计,回归,假设测试和样本大小计算.
- 方法通常针对特定的不成比例危险场景而具体.
- 编制了可用的技术的全面概述.
结论:
- 对于不成比例危险的统计方法存在多样性,但没有单一的共识方法.
- 该审查提供了一个结构化的概述,并为选择合适的方法提供了指导.
- 进一步的研究可能会从标准化报告和这些先进技术的应用中受益.
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