S. MacEachern

Assessing Unmeasured Confounding in Observational Research via Bayesian Semiparametric Modeling

This commentary first introduces a Bayesian semiparametric model for causal inference, then presents a sensitivity analysis strategy for the Gaussian process model, which is easily interpretable and avoids restrictive parametric outcome assumptions.