一个统计框架,用于规划和分析可重复性测试复试研究
Moritz Fabian Danzer1, Maria Eveslage1, Dennis Görlich1
1Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany.
Statistical methods in medical research
|February 1, 2024
概括
准确的测量可重复性对于评估生物标志物至关重要. 本研究引入了测试复试研究中样本大小计算的框架,以确保纵向研究中可靠的生物标志物评估.
科学领域:
- 生物标志物研究的研究.
- 纵向研究设计 纵向研究设计
- 统计方法学的统计方法.
背景情况:
- 定量生物标志物有助于早期评估治疗反应和疾病进展.
- 生物标志物测量具有固有的随机变异性,可能掩盖真实变化.
- 在纵向生物标志物研究之前,评估测量可重复性至关重要.
研究的目的:
- 开发一个全面的框架,用于测试-重新测试研究的样本大小计算.
- 在纵向研究中建立评估生物标志物评估质量的标准.
- 为了能够灵活地确定试验重试研究的样本大小.
主要方法:
- 测量可重复性的量化,使用测试重试研究中的可重复性系数.
- 基于纵向评估质量标准的样本大小计算的新框架的开发.
- 适用现有试验复试研究的追溯评估框架.
主要成果:
- 已经建立了一个灵活的框架,用于测试-重新测试研究中的样本大小计算.
- 该框架将样本大小与纵向研究中生物标志物评估的期望质量联系起来.
- 拟议的方法允许对先前的试验-再试验研究样本大小进行回顾性评估.
结论:
- 开发的框架解决了在测试-再测试研究中样本大小计算指南的缺乏问题.
- 准确估计可重复性系数对于可靠的纵向生物标志物评估至关重要.
- 该框架提高了临床研究中定量生物标志物利用的质量和可靠性.
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