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关联措施的选择会影响多病症网络的可视化和组成
Mohammad Reza Baneshi1, Annette Dobson2, Gita D Mishra2
1Australian Women and Girls' Health Research Centre, School of Public Health, Faculty of Medicine, The University of Queensland, Level 3 Public Health Building, 288 Herston Rd, Herston, QLD, 4006, Australia. m.baneshi@uq.edu.au.
BMC medical research methodology
|July 23, 2024
概括
对多病症的网络分析表明,不同的统计权重产生了不同的结果. 对于强大的可视化,专注于通过多种统计方法识别的条件对.
科学领域:
- 老年学是一门学科.
- 网络科学 网络科学
- 流行病学 流行病学
背景情况:
- 网络分析是理解多病态模式的常见工具.
- 条件之间的关联强度在网络分析中被用作权重.
- 网络分析结果对选择重量的稳定性尚未得到充分理解.
研究的目的:
- 检查网络分析结果对多病症的稳定性,以选择统计权重.
- 在网络分析中比较不同的统计数据来测量条件关联.
主要方法:
- 利用来自澳大利亚死亡证明的数据,研究了85岁以上的女性27种慢性疾病.
- 计算了五个关联统计数据:赔率比 (OR),升值,phi相关性,索尔顿等号指数 (SCI) 和正常化关节频率 (NF).
- 根据每个统计数据的权重,对前10%的条件对进行了网络分析.
主要成果:
- 在56个顶级对中,13个对在所有五个统计数据中都是一致的.
- 根据所选择的统计数据,网络结构和社区识别的差异很大.
- 低患病率的疾病显示出不同的中心性模式,取决于所使用的重量指标 (例如,OR/lift与SCI).
结论:
- 用于估计体重的不同统计数据导致了多病症研究中不同的网络结构.
- 对于探索性分析,多重权重可以识别潜在的条件对进行进一步研究.
- 为了实现强大而节的网络可视化,优先考虑通过多种统计方法识别的条件对.
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