Causal Inference and Observational Research: The Utility of Twins.

Causal Inference and Observational Research: The Utility of Twins.
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DOI:
10.1177/1745691610383511
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发表时间:
2010-09
期刊:
Perspectives on psychological science : a journal of the Association for Psychological Science
影响因子:
--
通讯作者:
Christensen K
Christensen K
中科院分区:
其他
文献类型:
--
作者:
McGue M;Osler M;Christensen K

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有效的因果推理是理论和应用心理学进步的核心。尽管随机实验被广泛认为是确定特定暴露是否增加某些特定结果可能性的金标准,但实验并不总是可行的,在某些情况下可能导致因果效应的偏倚估计。或者,标准的观察方法受到混杂、反向因果关系和暴露的非随机分布(即,选择)。我们描述了因果关系的反事实模型,并将其应用于观察性研究中因果推理的挑战,特别关注衰老。我们认为,研究双胞胎对不一致的曝光,特别是不一致的单卵双胞胎,提供了一个有用的模拟理想化的反事实设计。对老龄化中不和谐双胞胎研究的回顾表明,它们与生活方式因素对重要晚年结局的因果影响一致,但并不能明确确立。尽管如此,现有的研究数量很少,并且有明显的局限性,在解释其结果时并不总是考虑到这些局限性。结论是,双胞胎研究者可以更多地利用不和谐的双胞胎设计作为一种方法,以加强因果关系的推论在观察研究。
Valid causal inference is central to progress in theoretical and applied psychology. Although the randomized experiment is widely considered the gold standard for determining whether a given exposure increases the likelihood of some specified outcome, experiments are not always feasible and in some cases can result in biased estimates of causal effects. Alternatively, standard observational approaches are limited by the possibility of confounding, reverse causation, and the nonrandom distribution of exposure (i.e., selection). We describe the counterfactual model of causation and apply it to the challenges of causal inference in observational research, with a particular focus on aging. We argue that the study of twin pairs discordant on exposure, and in particular discordant monozygotic twins, provides a useful analog to the idealized counterfactual design. A review of discordant-twin studies in aging reveals that they are consistent with, but do not unambiguously establish, a causal effect of lifestyle factors on important late-life outcomes. Nonetheless, the existing studies are few in number and have clear limitations that have not always been considered in interpreting their results. It is concluded that twin researchers could make greater use of the discordant-twin design as one approach to strengthen causal inferences in observational research.
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