Network Influence with Latent Homophily and Measurement Error. (arXiv:2203.14223v2 [stat.ME] UPDATED)

Modeling social influence on outcomes of network-connected individuals is a
central research question in several scientific disciplines. However, network
influence cannot be identified from observational data because it is confounded
with unobserved homophily. We propose a latent homophily-adjusted Spatial
Autoregressive model (SAR) for networked responses to identify the causal
contagion effects. The latent homophily is estimated from the spectral
embedding of the network's adjacency matrix. We further develop maximum
likelihood estimators for the parameters of the SAR model when covariates …

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