# Propensity Score Modeling: Key Challenges When Moving Beyond the No-Interference Assumption

arXiv: https://arxiv.org/abs/2208.06533 · HTML: https://mlsanity.com/paper/2208.06533/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Aug 2022.

## Built on by (most cited first, 1 of 1)

- [Generalization bound for estimating causal effects from observational network data](https://mlsanity.com/paper/2308.04011/) (2023)

## Abstract (arXiv)

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.