Taking Selection Seriously in Correlational Studies of Child Development: A Call for Sensitivity Analyses
Taking Selection Seriously in Correlational Studies of Child Development: A Call for Sensitivity Analyses
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DOI：
10.1111/cdep.12343
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发表时间：
2019-10-04
影响因子：
6.4
通讯作者：
Zachrisson, Henrik D.
中科院分区：
文献类型：
--
作者：
Dearing, Eric;Zachrisson, Henrik D.
相关研究在积累儿童发展知识方面发挥了重要作用。然而，结果是，我们常常很难做出因果推论。人们担心的是选择效应：当孩子们没有被随机分配到条件中时，预先存在的生物、心理或社会因素可能会影响相关性。在本文中，我们提请注意的敏感性分析，统计技术估计稳健性或脆弱性的结果在潜在的选择效应的光。我们强调了Oster（2019）最近开发的比例系数方法，该方法不需要对省略选择变量的数量进行假设。比例系数表明，相对于观察到的协变量，未观察到的选择因素的影响需要多大才能使结果无效。我们提供了两个实证例子来证明这种方法与儿童发展研究人员使用的其他方法的价值。
Correlational studies have played a major role in building our cumulative knowledge on child development. Yet as a result, we often have difficulty making causal inferences. The concern is selection effects: When children have not been randomly assigned to conditions, pre-existing biological, psychological, or social factors may bias correlations. In this article, we draw attention to sensitivity analyses, statistical techniques for estimating the robustness or fragility of results in light of potential selection effects. We highlight the coefficient of proportionality method recently developed by Oster (2019), which does not require assumptions about the number of omitted selection variables. The coefficient of proportionality provides an indication of how large the impact of unobserved selection factors would need to be-relative to observed covariates-to nullify a result. We offer two empirical examples to demonstrate the value of this method compared with other approaches used by child development researchers.