Mediation analysis with graph mediator.

IF 1.8 3区 数学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Yixi Xu, Yi Zhao
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引用次数: 0

Abstract

This study introduces a mediation analysis framework when the mediator is a graph. A Gaussian covariance graph model is assumed for graph presentation. Causal estimands and assumptions are discussed under this presentation. With a covariance matrix as the mediator, a low-rank representation is introduced and parametric mediation models are considered under the structural equation modeling framework. Assuming Gaussian random errors, likelihood-based estimators are introduced to simultaneously identify the low-rank representation and causal parameters. An efficient computational algorithm is proposed and asymptotic properties of the estimators are investigated. Via simulation studies, the performance of the proposed approach is evaluated. Applying to a resting-state fMRI study, a brain network is identified within which functional connectivity mediates the sex difference in the performance of a motor task.

使用图中介的中介分析。
本研究引入了一个以图为中介的中介分析框架。图的表示采用高斯协方差图模型。本报告将讨论因果估计和假设。以协方差矩阵为中介,引入低秩表示,在结构方程建模框架下考虑参数化中介模型。在假设高斯随机误差的情况下,引入基于似然的估计器来同时识别低秩表示和因果参数。提出了一种有效的计算算法,并研究了估计量的渐近性质。通过仿真研究,对该方法的性能进行了评价。应用静息状态fMRI研究,确定了一个大脑网络,其中功能连接介导了运动任务表现的性别差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biostatistics
Biostatistics 生物-数学与计算生物学
CiteScore
5.10
自引率
4.80%
发文量
45
审稿时长
6-12 weeks
期刊介绍: Among the important scientific developments of the 20th century is the explosive growth in statistical reasoning and methods for application to studies of human health. Examples include developments in likelihood methods for inference, epidemiologic statistics, clinical trials, survival analysis, and statistical genetics. Substantive problems in public health and biomedical research have fueled the development of statistical methods, which in turn have improved our ability to draw valid inferences from data. The objective of Biostatistics is to advance statistical science and its application to problems of human health and disease, with the ultimate goal of advancing the public''s health.
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