Mixed-Effect Time-Varying Network Model and Application in Brain Connectivity Analysis

Jingfei Zhang, Will Wei Sun and Lexin Li

Journal of the American Statistical Association, 2020, vol. 115, issue 532, 2022-2036

Abstract: Time-varying networks are fast emerging in a wide range of scientific and business applications. Most existing dynamic network models are limited to a single-subject and discrete-time setting. In this article, we propose a mixed-effect network model that characterizes the continuous time-varying behavior of the network at the population level, meanwhile taking into account both the individual subject variability as well as the prior module information. We develop a multistep optimization procedure for a constrained likelihood estimation and derive the associated asymptotic properties. We demonstrate the effectiveness of our method through both simulations and an application to a study of brain development in youth. Supplementary materials for this article are available online.

Date: 2020
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DOI: 10.1080/01621459.2019.1677242

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