Statistical Power for Causally Defined Indirect Effects in Group-Randomized Trials With Individual-Level Mediators
Statistical Power for Causally Defined Indirect Effects in Group-Randomized Trials With Individual-Level Mediators
复制标题
在个体水平中介变量的分组随机试验中因果定义的间接效应的统计功效
DOI：
10.3102/1076998617695506
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发表时间：
2017
影响因子：
2.4
通讯作者：
Kyle Cox
中科院分区：
文献类型：
--
作者：
Ben Kelcey;N. Dong;Jessaca K. Spybrook;Kyle Cox
促进关于治疗的总效应和间接效应的推论的设计可能提供对干预措施的更全面的描述，因为它们可以通过对实质性理论所暗示的因果关系的全面研究来补充“什么有效”的问题。绘制设计的灵敏度以检测这些效应至关重要，因为它直接决定了研究人员在现实样本量下可以对行为理论产生影响的证据类型。在这项研究中，我们开发了封闭形式的表达式来估计在两个水平的随机分组研究中检测因果定义的间接效应的方差和功效，这些研究检查了个体水平的介质（即，2-1-1调解）。我们制定我们的方法范围内的典型的多层次调解模型和锚他们的解释在潜在的结果框架。结果提供了功率分析公式，该公式将计算简化为主要路径系数的简单函数（例如，治疗-介体和介体-结果关系）和常见的概括统计（例如，组内相关系数）。探索这些公式表明，组随机设计可以很好地检测间接影响时，精心策划。功率公式在PowerUp软件（causeevaluation.org）中实现。
Designs that facilitate inferences concerning both the total and indirect effects of a treatment potentially offer a more holistic description of interventions because they can complement “what works” questions with the comprehensive study of the causal connections implied by substantive theories. Mapping the sensitivity of designs to detect these effects is of critical importance because it directly governs the types of evidence researchers can bring to bear on theories of action under realistic sample sizes. In this study, we develop closed-form expressions to estimate the variance of and the power to detect causally defined indirect effects in two-level group-randomized studies examining individual-level mediators (i.e., 2-1-1 mediation). We formulate our approach within the purview of typical multilevel mediation models and anchor their interpretation in the potential outcomes framework. The results provide power analysis formulas that reduce calculations to simple functions of the primary path coefficients (e.g., treatment–mediator and mediator–outcome relationships) and common summary statistics (e.g., intraclass correlation coefficients). Probing these formulas suggests that group-randomized designs can be well powered to detect indirect effects when carefully planned. The power formulas are implemented in the PowerUp software (causalevaluation.org).
影响因子：
7
作者：
MacKinnon, DP;Lockwood, CM;Sheets, V
通讯作者：
Sheets, V