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相关概念视频

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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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相关实验视频

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在连接和断开网络中进行组件网络元分析的模型选择:模拟研究.

Maria Petropoulou1, Gerta Rücker1, Stephanie Weibel2

  • 1Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Stefan-Meier-Straße 26, 79104, Freiburg, Germany.

BMC medical research methodology
|June 14, 2023
PubMed
概括

组件网络元分析 (CNMA) 可以有效地分析连接网络中的干预. 然而,它在断开的网络中的使用是有问题的,特别是没有强有力的证据表明添加组件效应.

关键词:
组件网络的元分析.断开连接的网络 断开的网络模型选择 模型选择多组件干预措施是多组件干预措施.模拟模拟是为了模拟.

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科学领域:

  • 生物统计学 生物统计学
  • 临床流行病学临床流行病学
  • 医疗保健服务研究 医疗服务研究

背景情况:

  • 网络元分析 (NMA) 估计和排名干预效应.
  • 组件网络元分析 (CNMA) 通过分析多组件干预的单个组件来扩展NMA.
  • CNMA可以使用共同组件重新连接断开的网络,并允许放松附加性假设.

研究的目的:

  • 评估CNMA的前性模型选择策略,以放松连接和断开网络中的附加性假设.
  • 描述创建断开网络的程序,以评估模型选择属性.
  • 应用和比较CNMA方法使用模拟数据和现实世界的临床审查.

主要方法:

  • 采用了CNMA的前性模型选择策略.
  • 开发了一种程序来生成断开连接的网络进行评估.
  • 应用于模拟数据的方法和科克莱恩关于术后恶心和吐干预措施的评论.
  • 使用平均平均平方误差和覆盖概率评估模型性能.

主要成果:

  • 在连接网络中,CNMA模型表现出良好的性能,在添加性适当时,作为标准NMA的替代品.
  • 对于断开的网络,只有当有强有力的临床证据支持添加性时,才建议添加CNMA.
  • 模型选择策略的有效性在各种网络结构中得到了评估.

结论:

  • 组件网络元分析 (CNMA) 是连接网络的可行方法.
  • 在断开网络中应用CNMA需要仔细考虑,并且通常是可疑的.
  • 在断开网络中添加CNMA只应在有强有力的临床理由的情况下使用.