Bayesian nonparametric generative models for causal inference with missing at random covariates.
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DOI: 10.1111/biom.12875
Abstract: We propose a general Bayesian nonparametric (BNP) approach to causal inference in the point treatment setting. The joint distribution of the observed data (outcome, treatment, and confounders) is modeled using an enriched Dirichlet process. The… read more here.
Keywords: bayesian nonparametric; causal inference; nonparametric generative; model ... See more keywords