4 papers · 1 filter
Distributional Balancing for Causal Inference: A Unified Framework via Characteristic Function Distance
Diptanil Santra, Guanhua Chen, Chan Park
Weighting methods are essential tools for estimating causal effects in observational studies, with the goal of balancing pre-treatment covariates across treatment groups. Tradition…
Nonparametric Inference with an Instrumental Variable under a Separable Binary Treatment Choice Model
Chan Park, Eric Tchetgen Tchetgen
Instrumental variable (IV) methods are widely used to infer treatment effects in the presence of unmeasured confounding. In this paper, we study nonparametric inference with an IV…
Proximal Causal Inference for Conditional Separable Effects
Chan Park, Mats Stensrud, Eric Tchetgen Tchetgen
Scientists regularly pose questions about treatment effects on outcomes conditional on a post-treatment event. However, causal inference in such settings requires care, even in per…
Regression-Based Proximal Causal Inference
Jiewen Liu, Chan Park, Kendrick Li +1
Negative controls are increasingly used to evaluate the presence of potential unmeasured confounding in observational studies. Beyond the use of negative controls to detect the pre…