Causal inference from observational data: A Bayesian predictive approach - Arjas, Elja (Causality, 2012)
Keywords: causal inference from observational data, Bayesian predictive; causality, and temporality, confounding, statistical inference; effects of causes, in terms of posterior predictive distributions/expectations; G‐computation algorithm, on model parameter and treatment assignments; marked point formalism, and latent variables and developments; marked point sequence and counting processes, in continuous time; MATHEMATICS; potential, or counterfactual outcomes, drawback of sequential regimes; Robins' model, extension of Rubin causal model to sequential designs; unconfounded inference conditions, against bias in causal conclusions; unconfounded statistical inferences, from observational data