Extrapolating Treatment Effects in Multi-Cutoff Regression Discontinuity Designs

In nonexperimental settings, the regression discontinuity (RD) design is one of the most credible identification strategies for program evaluation and causal inference. However, RD treatment effect…

Biased Encouragements and Heterogeneous Effects in an Instrumental Variable S…

We investigate the efficacy of surgical versus nonsurgical management for two gastrointestinal conditions, colitis and diverticulitis, using observational data. We deploy an instrumental variable d…

Comparing Covariate Prioritization via Matching to Machine Learning Methods f…

When investigators seek to estimate causal effects, they often assume that selection into treatment is based only on observed covariates. Under this identification strategy, analysts must adjust fo…

Randomization Inference for Outcomes with Clumping at Zero

Survivor-Complier Effects in the presence of Selection on Treatment, With App…

Optimal Multilevel Matching in Clustered Observational Studies : A Case Study…