本文介绍了来自多个研究的个体参与者数据(IPD)的元分析中介分析方法。中介分析评估干预对健康结果的有效性是否由于干预所针对的关键行为的变化而发生。然而,个别试验通常在统计学上不足以检验调解假说.在元分析背景下评估调解的现有方法受到它们对汇总数据的依赖的限制;因此,研究结果可能与与感兴趣途径无关的研究水平差异相混淆.为了克服现有元分析调解方法的局限性,我们使用结构方程模型(SEM)的一阶段估计方法,将来自多项研究的IPD结合起来进行中介分析.这种方法(1)说明了研究中参与者的聚集,(2)通过多重插补来容纳缺失的数据,和(3)允许关于间接(即,通过自举置信区间介导)效应。我们使用了来自INTEGRATE项目的数据(来自10项研究的N=3691)(Mun等人。成瘾行为心理学,29,34-48,2015),通过测试使用保护性行为策略的改进是否介导了大学生对酒精相关问题的简短动机干预的有效性,来说明SEM方法进行荟萃分析调解分析。为了促进方法的应用,我们在R中提供带注释的计算机代码和用于复制的数据。在实质性层面,独立的个性化反馈干预通过更多地使用保护性行为策略来减少酒精相关问题;然而,跨策略的净中介效应规模较小,平均而言。
This paper introduces a meta-analytic mediation analysis approach for individual participant data (IPD) from multiple studies. Mediation analysis evaluates whether the effectiveness of an intervention on health outcomes occurs because of change in a key behavior targeted by the intervention. However, individual trials are often statistically underpowered to test mediation hypotheses. Existing approaches for evaluating mediation in the meta-analytic context are limited by their reliance on aggregate data; thus, findings may be confounded with study-level differences unrelated to the pathway of interest. To overcome the limitations of existing meta-analytic mediation approaches, we used a one-stage estimation approach using structural equation modeling (SEM) to combine IPD from multiple studies for mediation analysis. This approach (1) accounts for the clustering of participants within studies, (2) accommodates missing data via multiple imputation, and (3) allows valid inferences about the indirect (i.e., mediated) effects via bootstrapped confidence intervals. We used data (N = 3691 from 10 studies) from Project INTEGRATE (Mun et al. Psychology of Addictive Behaviors, 29, 34-48, 2015) to illustrate the SEM approach to meta-analytic mediation analysis by testing whether improvements in the use of protective behavioral strategies mediate the effectiveness of brief motivational interventions for alcohol-related problems among college students. To facilitate the application of the methodology, we provide annotated computer code in R and data for replication. At a substantive level, stand-alone personalized feedback interventions reduced alcohol-related problems via greater use of protective behavioral strategies; however, the net-mediated effect across strategies was small in size, on average.