Department of Psychology, Arizona State University.
J Couns Psychol. 2017 Nov;64(6):659-671. doi: 10.1037/cou0000242.
Psychology researchers are often interested in mechanisms underlying how randomized interventions affect outcomes such as substance use and mental health. Mediation analysis is a common statistical method for investigating psychological mechanisms that has benefited from exciting new methodological improvements over the last 2 decades. One of the most important new developments is methodology for estimating causal mediated effects using the potential outcomes framework for causal inference. Potential outcomes-based methods developed in epidemiology and statistics have important implications for understanding psychological mechanisms. We aim to provide a concise introduction to and illustration of these new methods and emphasize the importance of confounder adjustment. First, we review the traditional regression approach for estimating mediated effects. Second, we describe the potential outcomes framework. Third, we define what a confounder is and how the presence of a confounder can provide misleading evidence regarding mechanisms of interventions. Fourth, we describe experimental designs that can help rule out confounder bias. Fifth, we describe new statistical approaches to adjust for measured confounders of the mediator-outcome relation and sensitivity analyses to probe effects of unmeasured confounders on the mediated effect. All approaches are illustrated with application to a real counseling intervention dataset. Counseling psychologists interested in understanding the causal mechanisms of their interventions can benefit from incorporating the most up-to-date techniques into their mediation analyses. (PsycINFO Database Record
心理学研究人员通常对随机干预如何影响物质使用和心理健康等结果的潜在机制感兴趣。中介分析是一种常见的统计方法，用于研究心理机制，在过去 20 年中受益于令人兴奋的新方法改进。最新的发展之一是使用因果推断的潜在结果框架估计因果中介效应的方法。流行病学和统计学中发展起来的潜在结果方法对理解心理机制具有重要意义。我们旨在提供这些新方法的简明介绍和说明，并强调调整混杂因素的重要性。首先，我们回顾了用于估计中介效应的传统回归方法。其次，我们描述了潜在结果框架。第三，我们定义了什么是混杂因素，以及混杂因素的存在如何为干预机制提供误导性证据。第四，我们描述了有助于排除混杂因素偏差的实验设计。第五，我们描述了用于调整中介-结果关系中测量混杂因素的新统计方法和敏感性分析，以探究未测量混杂因素对中介效应的影响。所有方法都应用于真实的咨询干预数据集进行说明。有兴趣了解干预措施因果机制的咨询心理学家可以从将最新技术纳入其中介分析中受益。
