11 papers
A Characterization of the Orthocomplement of the Tangent Space of Semiparametric Markov Models
Trung Phung, Ilya Shpitser
Graphical models are ubiquitous in social and empirical science as they are intuitive and easy to use. These models belong to the broader class of Markov models, defined using sole…
Proximal Identification and Estimation in Front-Door Causal Structures with Unobserved Confounding of the Mediator
Helen Guo, Beatrix Yaxin Wen, Ilya Shpitser
Unobserved confounding is a fundamental obstacle in causal inference problems. In the graphical modeling literature, a general theory has been developed that allows identification…
Multiply Robust Causal Mediation Analysis with Continuous Treatments
Yizhen Xu, AmirEmad Ghassami, Numair Sani +1
In many applications, researchers are interested in the direct and indirect causal effects of a treatment or exposure on an outcome of interest. Mediation analysis offers a rigorou…
Exploiting independence constraints for efficient estimation of bounds on causal effects in the presence of unmeasured confounding
Ting-Hsuan Chang, Caleb H. Miles, Ilya Shpitser +2
Causal graphs may inform covariate adjustment for estimating causal effects and improve estimation efficiency by exploiting the graphical structure. In many applications, however,…
Proximal Causal Inference for Hidden Outcomes
Helen Guo, Ilya Shpitser, Elizabeth L. Ogburn
Methods that rely on proxies, without imposing strong parametric structure, are increasingly used to deal with unobserved variables in causal inference. One influential line of thi…
Comparing Two Proxy Methods for Causal Identification
Helen Guo, Elizabeth L. Ogburn, Ilya Shpitser
Identifying causal effects in the presence of unmeasured variables is a fundamental challenge in causal inference, for which proxy variable methods have emerged as a powerful solut…