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Robust Weighted Triangulation of Causal Effects Under Model Uncertainty
Rohit Bhattacharya, Ina Ocelli, Ted Westling
A fundamental challenge in causal inference with observational data is correct specification of a causal model. When there is model uncertainty, analysts may seek to use estimates…
Response to Discussions of "Causal and Counterfactual Views of Missing Data Models"
Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser +1
We are grateful to the discussants, Levis and Kennedy [2025], Luo and Geng [2025], Wang and van der Laan [2025], and Yang and Kim [2025], for their thoughtful comments on our paper…
Recursive Equations For Imputation Of Missing Not At Random Data With Sparse Pattern Support
Trung Phung, Kyle Reese, Ilya Shpitser +1
A common approach for handling missing values in data analysis pipelines is multiple imputation via software packages such as MICE (Van Buuren and Groothuis-Oudshoorn, 2011) and Am…
Causal and Counterfactual Views of Missing Data Models
Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser +1
It is often said that the fundamental problem of causal inference is a missing data problem -- the comparison of responses to two hypothetical treatment assignments is made difficu…