在一个随机交叉试验中,对配对配对混合模型,以共同建模多变量纵向结果,随机交叉试验
Moses Mwangi1,2, Geert Molenberghs1,3, Edmund Njeru Njagi4
1I-BioStat, Universiteit Hasselt, Diepenbeek, Belgium.
Biometrical journal. Biometrische Zeitschrift
|March 19, 2024
概括
高剂量的盐显著降低了妇女和儿童的血压 (BP). 这项研究开发了一种灵活的零碎关节模型 (PLME) 来分析复杂的纵向营养和血压数据,其性能优于现有方法.
科学领域:
- 生物统计学 生物统计学
- 营养流行病学 营养流行病学
- 公共卫生 公共卫生
背景情况:
- 纵向数据分析需要复杂的模型来理解多个相关结果之间的关联.
- 高维和聚类纵向数据为联合建模提出了计算挑战.
- 了解摄入量对血压的影响对于公共健康至关重要.
研究的目的:
- 开发和评估一个灵活的零碎联合模型 (PLME) 来分析六个相关的纵向结果.
- 研究高剂量与低剂量盐与妇女和儿童的血压 (BP) 之间的关联.
- 在交叉试验环境中,将拟议的PLME模型与斯-肯沃德-默多克-埃伦伯格 (JKME) 模型的性能进行比较.
主要方法:
- 来自肯尼亚2x2随机交叉试验的数据分析.
- 灵活的零件式关节模型 (PLME) 的应用,从Mwangi等人扩展. (2021年). 在2021年.
- 适应15个双变的一般线性混合模型,并使用伪概率理论进行推理.
- 与斯-肯沃德-默多克-埃伦伯格 (JKME) 交叉试验方法的比较.
- 通过模拟研究来验证模拟交叉车设计.
主要成果:
- 与低剂量的盐相比,高剂量的盐显著降低了静缩血压 (SBP) 和腹缩血压 (DBP).
- 在SBP和DBP之间观察到强烈的正相关性,表明相关的进化趋势.
- 在女性和儿童中,尿度 (UIC) 和血压之间发现了适度强的反向关系.
- PLME模型在估计随机效应和黑塞矩阵方面表现出卓越的性能,实现了更好的模型趋同.
- PLME模型允许更复杂的匹配,包括随机拦截和斜率,与JKME模型不同,该模型仅限于随机拦截.
结论:
- 盐中高剂量的有效降低妇女和儿童的血压.
- 拟议的多变量联合PLME模型为复杂的纵向数据分析提供了灵活和计算效率高的方法.
- PLME模型为JKME模型提供了一个可行的替代方案,特别是当将随机斜率纳入交叉设计中以改进数据拟合时.
- 该研究强调了考虑联合建模相关的纵向结果的重要性,以准确地捕捉它们的关联和影响.
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