Causal Inference in Longitudinal Data under Unknown Interference
arXiv:2106.15074
Abstract
In longitudinal studies where units are embedded in space or a social network, interference may arise, meaning that a unit's outcome can depend on treatment histories of others. The presence of interference poses significant challenges for causal inference, particularly when the interference structure -- how a unit's outcome responds to others' influences -- is complex, heterogeneous, and unknown to researchers. This paper develops a general framework for identifying and estimating both direct and spillover effects of treatment histories under minimal assumptions about the interference structure. We introduce a class of causal estimands that capture the effects of treatment histories at any specified proximity level and show that they can be represented by a modified marginal structural model. Under sequential exchangeability, these estimands are identifiable and can be estimated using inverse probability weighting. We derive conditions for consistency and asymptotic normality of the estimators and provide procedures for constructing asymptotically conservative confidence intervals. The method's utility is demonstrated through applications in both social science and biomedical settings.
References in corpus (10)
- A new method of normal approximation
- A short survey of Stein's method
- Limit Theorems for Network Dependent Random Variables
- Finite-Sample Optimal Estimation and Inference on Average Treatment Effects Under Unconfoundedness
- Central limit theorems via Stein's method for randomized experiments under interference
- Random Graph Asymptotics for Treatment Effect Estimation under Network Interference
- Identification of Causal Diffusion Effects Under Structural Stationarity
- Causal Inference in Possibly Nonlinear Factor Models
- Causal Inference with Spatio-temporal Data: Estimating the Effects of Airstrikes on Insurgent Violence in Iraq
- Adjusting for Unmeasured Confounding in Marginal Structural Models with Propensity-Score Fixed Effects