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Causal inference from randomized trials in social epidemiology.

机译:社会流行病学随机试验的因果推论。

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摘要

Social epidemiology is the study of relations between social factors and health status in populations. Although recent decades have witnessed a rapid development of this research program in scope and sophistication, causal inference has proven to be a persistent dilemma due to the natural assignment of exposure level based on unmeasured attributes of individuals, which may lead to substantial confounding. Some optimism has been expressed about randomized social interventions as a solution to this long-standing inferential problem. We review the causal inference problem in social epidemiology, and the potential for causal inference in randomized social interventions. Using the example of a currently on-going intervention that randomly assigns families to non-poverty housing, we review the limitations to causal inference even under experimental conditions and explain which causal effects become identifiable. We note the benefit of using the randomized trial as a conceptual model, even for design and interpretation of observational studies in social epidemiology.
机译:社会流行病学是对人口中社会因素与健康状况之间关系的研究。尽管最近几十年见证了该研究计划在范围和复杂性方面的快速发展,但因果推断是一个持续的难题,这是由于根据未测个体的自然属性对暴露水平进行了自然分配,这可能导致严重的混淆。对于这种长期存在的推论问题的解决方案,人们对随机的社会干预表示了一些乐观。我们回顾了社会流行病学中的因果推断问题,以及随机社会干预中因果推断的潜力。以当前正在进行的干预为例,该干预将家庭随机分配给非贫困住房,我们甚至回顾了因果推理在实验条件下的局限性,并解释了哪些因果效应变得可识别。我们注意到使用随机试验作为概念模型的好处,甚至对于社会流行病学中观察性研究的设计和解释也是如此。

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