257 citations · 1k across the 41 of their papers we have counts for
42 papers
Potential Outcome and Decision Theoretic Foundations for Statistical Causality
Thomas S. Richardson, James M. Robins
In a recent paper published in the Journal of Causal Inference, Philip Dawid has described a graphical causal model based on decision diagrams. This article describes how single-wo…
The m-connecting imset and factorization for ADMG models
Bryan Andrews, Gregory F. Cooper, Thomas S. Richardson +1
Directed acyclic graph (DAG) models have become widely studied and applied in statistics and machine learning -- indeed, their simplicity facilitates efficient procedures for learn…
Discussion of 'Estimating time-varying causal excursion effect in mobile health with binary outcomes' by T. Qian et al
F. Richard Guo, Thomas S. Richardson, James M. Robins
We discuss the recent paper on "excursion effect" by T. Qian et al. (2020). We show that the methods presented have close relationships to others in the literature, in particular t…
An Interventionist Approach to Mediation Analysis
James M. Robins, Thomas S. Richardson, Ilya Shpitser
Judea Pearl's insight that, when errors are assumed independent, the Pure (aka Natural) Direct Effect (PDE) is non-parametrically identified via the Mediation Formula was `path-bre…
Multivariate Counterfactual Systems And Causal Graphical Models
Ilya Shpitser, Thomas S. Richardson, James M. Robins
Among Judea Pearl's many contributions to Causality and Statistics, the graphical d-separation} criterion, the do-calculus and the mediation formula stand out. In this chapter we s…
Estimation of local treatment effects under the binary instrumental variable model
Linbo Wang, Yuexia Zhang, Thomas S. Richardson +1
Instrumental variables are widely used to deal with unmeasured confounding in observational studies and imperfect randomized controlled trials. In these studies, researchers often…