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Correspondent inference theory, proposed by Jones and Davis in 1965, seeks to explain how individuals infer stable personality traits from observed behaviors. It suggests that people attribute actions to underlying dispositions rather than external circumstances, particularly when the behavior appears intentional and socially significant.Voluntary Behavior and Dispositional AttributionAccording to this theory, individuals are more likely to attribute behavior to personal traits when it appears...
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Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
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Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
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Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3
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Minhao Yao1, Anqi Wang2, Xihao Li3,4

  • 1Centre for Biomedical Data Science, Duke-NUS Medical School, National University of Singapore, Singapore, Singapore.

Statistics in medicine
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概括
此摘要是机器生成的。

门德尔随机化 (MR) 是在健康研究中推断因果关系的强大工具. 这次审查系统地涵盖了MR方法,诸如无效仪器之类的挑战,以及应用科学家的实际指导.

关键词:
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科学领域:

  • 生物医学研究生物医学研究
  • 公共卫生 公共卫生
  • 遗传流行病学遗传流行病学

背景情况:

  • 门德尔随机化 (MR) 使用遗传变异作为工具变量来确定暴露和健康结果之间的因果关系.
  • MR提供了一种准实验方法来克服观察性研究中固有的混和反向因果关系.
  • 尽管MR具有实用性,但它面临着方法上的障碍,包括无效或弱的仪器和复杂的数据结构.

研究的目的:

  • 提供对因果推理的门德尔随机化 (MR) 方法的系统教程审查.
  • 为了澄清因果解释,比较研究设计,并为研究人员提供实际指导.
  • 为了应对诸如无效仪器和最近对omics数据的进展等挑战.

主要方法:

  • 用于因果推断的MR方法的系统概述.
  • 讨论用于检测和纠正无效和弱工具的策略.
  • 整合基于人口的与基于家庭的数据设计以及个人层面与总结层面的数据设计.

主要成果:

  • 一样本与两样本MR设计的比较及其局限性.
  • 对复杂情景 (例如,许多软弱的仪器,omics数据) 的最新方法论进展的总结.
  • 使用现实数据的示例应用,包括英国生物银行和阿尔茨海默病研究.

结论:

  • 本综述是方法学家和应用科学家在因果推理方面的教程参考.
  • 它强调了明确的因果关系问题和MR方法的实际应用.
  • 内容旨在加强MR在生物医学和公共卫生研究中的严格应用.