5 papers
Distributional Discontinuity Design
Kyle Schindl, Larry Wasserman
Regression discontinuity and kink designs are typically analyzed through mean effects, even when treatment changes the shape of the entire outcome distribution. To address this, we…
Causal Inference Using Augmented Epidemic Models
Heejong Bong, Valérie Ventura, Larry Wasserman
Epidemic models describe the evolution of a communicable disease over time. These models are often modified to include the effects of interventions (control measures) such as vacci…
Causal Geodesy: Counterfactual Estimation Along the Path Between Correlation and Causation
Kyle Schindl, Larry Wasserman
We introduce causal geodesy, a framework for studying the landscape of stochastic interventions that lie between the two extremes of performing no intervention, and performing a sh…
Robust Simulation Based Inference
Lorenzo Tomaselli, Valérie Ventura, Larry Wasserman
Simulation-Based Inference (SBI) is an approach to statistical inference where simulations from an assumed model are used to construct estimators and confidence sets. SBI is often…
Frequentist Inference for Semi-mechanistic Epidemic Models with Interventions
Heejong Bong, Valérie Ventura, Larry Wasserman
The effect of public health interventions on an epidemic are often estimated by adding the intervention to epidemic models. During the Covid-19 epidemic, numerous papers used such…