Design approaches to experimental mediation.
Design approaches to experimental mediation.
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DOI：
10.1016/j.jesp.2015.09.012
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发表时间：
2016-09
影响因子：
3.5
通讯作者：
MacKinnon DP
中科院分区：
文献类型：
--
作者：
Pirlott AG;MacKinnon DP
确定因果机制已成为实验社会心理学的基石，顶级社会心理学期刊的编辑们支持使用调解方法，特别是在可能的情况下（例如）。通常，实验社会心理学研究将参与者随机分配到自变量水平，测量中介变量和因变量，并假设中介变量对因变量产生因果影响。然而，参与者并不是随机分配到中介变量的水平，也就是说，中介变量和因变量之间的关系是相关的。虽然研究人员可能知道相关研究有混淆的风险，但在考虑随机分配参与者到自变量水平和测量中介（即“测量-中介”设计）时，这个问题似乎被遗忘了。实验操作中介提供了一种解决这些问题的方法，然而这些方法包含它们自己的一组挑战（例如，）。我们描述了针对中介的实验操作类型（证明中介对因变量的因果效应的操作和针对中介因果效应强度的操作）和实验设计类型（双随机化，并发双随机化和并行），提供了已发表的设计示例，并讨论了每种设计的优势和挑战。因此，本文的目标包括根据其挑战为中介操纵设计提供实用指南，并鼓励研究人员使用更严格的中介方法，因为中介操纵设计加强了推断中介变量对因变量因果关系的能力。
Identifying causal mechanisms has become a cornerstone of experimental social psychology, and editors in top social psychology journals champion the use of mediation methods, particularly innovative ones when possible (e.g.). Commonly, studies in experimental social psychology randomly assign participants to levels of the independent variable and measure the mediating and dependent variables, and the mediator is assumed to causally affect the dependent variable. However, participants are not randomly assigned to levels of the mediating variable(s), i.e., the relationship between the mediating and dependent variables is correlational. Although researchers likely know that correlational studies pose a risk of confounding, this problem seems forgotten when thinking about experimental designs randomly assigning participants to levels of the independent variable and measuring the mediator (i.e., “measurement-of-mediation” designs). Experimentally manipulating the mediator provides an approach to solving these problems, yet these methods contain their own set of challenges (e.g.,). We describe types of experimental manipulations targeting the mediator (manipulations demonstrating a causal effect of the mediator on the dependent variable and manipulations targeting the strength of the causal effect of the mediator) and types of experimental designs (double randomization, concurrent double randomization, and parallel), provide published examples of the designs, and discuss the strengths and challenges of each design. Therefore, the goals of this paper include providing a practical guide to manipulation-of-mediator designs in light of their challenges and encouraging researchers to use more rigorous approaches to mediation because manipulation-of-mediator designs strengthen the ability to infer causality of the mediating variable on the dependent variable.