alexpghayes / 2022-07-07-causal-network-regression-slides

Estimating indirect effects induced by homophily via spectral network regression

2022-07-07, Tianxi Li and Can Le Joint Lab Meeting

The last several years have seen a renewed and concerted effort to incorporate network data into standard tools for regression analysis, and to make network-linked data legible to practicing scientists. Thus far, this literature has primarily developed tools to infer associative relationships between nodal covariates and network structure. In contrast, we augment a statistical model for network regression with counterfactual assumptions and show how causal effects on a network can be partitioned into a direct effect that is uninfluenced by the network, and an indirect effect that is induced by homophily.