Propensity Score Modeling: Key Challenges When Moving Beyond the No-Interference Assumption
Methodology
2022-08-16 v1
Abstract
The paper presents some models for the propensity score. Considerable attention is given to a recently popular, but relatively under-explored setting in causal inference where the no-interference assumption does not hold. We lay out some key challenges in propensity score modeling under interference and present a few promising models based on existing works on mixed effects models.
Keywords
Cite
@article{arxiv.2208.06533,
title = {Propensity Score Modeling: Key Challenges When Moving Beyond the No-Interference Assumption},
author = {Hyunseung Kang and Chan Park and Ralph Trane},
journal= {arXiv preprint arXiv:2208.06533},
year = {2022}
}