"Functional Causal Mediation Analysis with an Application to Brain Connectivity"
Presenter: Dr. Martin Lindquist, Associate Professor, Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University
Mediation analysis is often used in the behavioral sciences to investigate the role of intermediate variables that lie on the causal path between a randomized treatment and an outcome variable. Typically, mediation is assessed using structural equation models (SEMs) with model coefficients interpreted as effects. In this paper we present an extension of SEMs to the functional data analysis (FDA) setting that allows the mediating variable to be a continuous function rather than a single scalar measure, thus providing the opportunity to study the functional effects of the mediator on the outcome. We provide sufficient conditions for identifying the average causal effects of the functional mediators using the extended SEM. The method is applied to data from a functional magnetic resonance imaging (fMRI) study of thermal pain that sought to determine whether activation in certain brain regions mediated the effect of applied temperature on self-reported pain.
Hosted by: Department of Biostatistics