Causal Inference and Developmental Psychology
Causal Inference and Developmental Psychology
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DOI：
10.1037/a0020204
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发表时间：
2010-11-01
影响因子：
4
通讯作者：
Foster, E. Michael
中科院分区：
文献类型：
--
作者：
Foster, E. Michael
因果推理是发展心理学的核心内容。该领域的许多关键问题都围绕着改善儿童及其家庭的生活。这些措施包括确定风险因素，如果以某种方式操纵，将促进儿童的发展。这样的任务本质上涉及因果推理：人们想知道风险因素是否真的导致了结果。在许多情况下，随机分配是不可能的，因此，心理学家必须依靠观察研究。这些研究确定了相关性，而这些相关性的因果解释需要额外的假设。发展心理学的研究通常依赖于各种形式的线性回归，但这种方法在因果推理方面存在局限性。幸运的是，各个领域的方法学发展正在为依赖于更合理假设的因果推理工具提供新的工具。本文描述了回归因果推理的局限性，并描述了新工具如何提供更好的因果推理。该讨论强调了正确识别协变量以从分析中包括（和排除）的重要性。本讨论考虑用于完成此任务的有向无环图。在选择了适当的协变量后，许多可用的方法都依赖于“可检验性”的假设。“这篇文章讨论了可验证性的含义，并考虑了这一假设的替代方案，如工具变量估计。最后，本文认为，在一个具体的研究问题，家庭结构对儿童发展的影响的背景下讨论的工具的使用。
Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether the risk factor actually causes outcomes. Random assignment is not possible in many instances, and for that reason, psychologists must rely on observational studies. Such studies identify associations, and causal interpretation of such associations requires additional assumptions. Research in developmental psychology generally has relied on various forms of linear regression, but this methodology has limitations for causal inference. Fortunately, methodological developments in various fields are providing new tools for causal inference tools that rely on more plausible assumptions. This article describes the limitations of regression for causal inference and describes how new tools might offer better causal inference. This discussion highlights the importance of properly identifying covariates to include (and exclude) from the analysis. This discussion considers the directed acyclic graph for use in accomplishing this task. With the proper covariates having been chosen, many of the available methods rely on the assumption of "ignorability." The article discusses the meaning of ignorability and considers alternatives to this assumption, such as instrumental variables estimation. Finally, the article considers the use of the tools discussed in the context of a specific research question, the effect of family structure on child development.