Chén Oliver Y, Crainiceanu Ciprian, Ogburn Elizabeth L, Caffo Brian S, Wager Tor D, Lindquist Martin A
Department of Biostatistics, Johns Hopkins University, USA.
Department of Psychology and Neuroscience, University of Colorado Boulder, 345 UCB, Boulder, CO 80309-0345, USA.
Biostatistics. 2018 Apr 1;19(2):121-136. doi: 10.1093/biostatistics/kxx027.
Mediation analysis is an important tool in the behavioral sciences for investigating the role of intermediate variables that lie in the path between a treatment and an outcome variable. The influence of the intermediate variable on the outcome is often explored using a linear structural equation model (LSEM), with model coefficients interpreted as possible effects. While there has been significant research on the topic, little work has been done when the intermediate variable (mediator) is a high-dimensional vector. In this work, we introduce a novel method for identifying potential mediators in this setting called the directions of mediation (DMs). DMs linearly combine potential mediators into a smaller number of orthogonal components, with components ranked based on the proportion of the LSEM likelihood each accounts for. This method is well suited for cases when many potential mediators are measured. Examples of high-dimensional potential mediators are brain images composed of hundreds of thousands of voxels, genetic variation measured at millions of single nucleotide polymorphisms (SNPs), or vectors of thousands of variables in large-scale epidemiological studies. We demonstrate the method using a functional magnetic resonance imaging study of thermal pain where we are interested in determining which brain locations mediate the relationship between the application of a thermal stimulus and self-reported pain.
中介分析是行为科学中用于研究介于治疗变量和结果变量之间的中间变量作用的重要工具。通常使用线性结构方程模型（LSEM）来探究中间变量对结果的影响，模型系数被解释为可能的效应。尽管关于该主题已有大量研究，但当中间变量（中介变量）是高维向量时，相关工作却很少。在这项研究中，我们引入了一种在这种情况下识别潜在中介变量的新方法，称为中介方向（DMs）。DMs将潜在中介变量线性组合成数量更少的正交分量，并根据每个分量在LSEM似然中所占的比例对其进行排序。该方法非常适合测量了许多潜在中介变量的情况。高维潜在中介变量的例子包括由数十万体素组成的脑图像、在数百万个单核苷酸多态性（SNP）处测量的基因变异，或大规模流行病学研究中数千个变量的向量。我们通过一项关于热痛的功能磁共振成像研究来展示该方法，在该研究中，我们感兴趣的是确定哪些脑区介导了热刺激的施加与自我报告的疼痛之间的关系。
