智能二进制:用于使用二进制结果测量的智能研究的新样本大小规划资源
John J Dziak1, Daniel Almirall2, Walter Dempsey2
1Institute for Health Research and Policy, University of Illinois at Chicago.
Multivariate behavioral research
|July 17, 2023
概括
具有二进制结果的顺序多重分配随机试验 (SMART) 可以通过重复测量来提高统计能力. 这项研究为这些重要的行为健康研究中的样本大小规划提供了新的方法.
科学领域:
- 心理学 心理学 心理学
- 行为健康研究 行为健康研究
- 临床试验 临床试验
背景情况:
- 顺序多重分配随机试验 (SMART) 对于根据心理和行为健康的个体需求量身定制干预措施至关重要.
- 现有的SMART样本大小规划存在局限性,特别是对于二进制结果,通常需要更大的样本大小.
- 目前对二进制结果SMART的方法不考虑基线或重复结果测量的功率增长.
研究的目的:
- 为解决二进制结果的SMARTs样本大小规划中的差距.
- 为两波重复测量提供模拟程序和公式二进制结果.
- 探索两个以上的结果测量场合的SMART的功率计算.
主要方法:
- 在两波重复测量SMART中开发了样本大小规划的模拟程序,具有二进制结果.
- 在这些设计中推导出样本大小估计的近似公式.
- 利用模拟来评估多次结果测量场合的研究的功率.
主要成果:
- 模拟结果表明与衍生公式的良好一致.
- 该研究证实,在特定条件下,至少包括一个重复结果测量可以显著提高统计能力.
- 在SMART中提供了计算功率的方法,结果测量次数不尽相同.
结论:
- 重复的结果测量提供了一种有价值的策略,以改善二进制结果的顺序多重分配随机试验的统计能力.
- 提供的模拟程序和公式为研究人员计划在心理和行为健康领域进行SMART研究提供了实用工具.
- 这些进步促进了针对个性化干预策略的更有效,更强大的研究设计.
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