Priming Bias Versus Post-Treatment Bias in Experimental Designs Jacob Brown (Harvard University), Matthew Blackwell (Harvard University), Sophie Hill (Harvard University), Kosuke Imai (Harvard... Read More Priming Bias Versus Post-Treatment Bias in Experimental Designs
Leveraging Observational Outcomes to Improve the Generalization of Experimental Results Melody Huang (University of California, Los Angeles), Erin Hartman (University of California, Los Angeles), Naoki Egami (Columbia... Read More Leveraging Observational Outcomes to Improve the Generalization of Experimental Results
A General Method for Detecting & Characterizing Interference in Field Experiments Connor Jerzak (Harvard University) Abstract: With the rise of online social networks, there has been growing interest in... Read More A General Method for Detecting & Characterizing Interference in Field Experiments
Causal Inference in Difference-in-Differences Designs under Uncertainty in Counterfactual Trends Thomas Leavitt (Columbia University) Abstract: Difference-in... Read More Causal Inference in Difference-in-Differences Designs under Uncertainty in Counterfactual Trends
Causal Inference Under Temporal and Spatial Interference Ye Wang (New York University) Abstract: Many social events and... Read More Causal Inference Under Temporal and Spatial Interference
Gaussian Process Models for Causal Inference With Time-Series Cross-Sectional Data Nuannuan Xiang and Kevin Quinn (University of Michigan) *Award for Best Graduate Student Poster - Methods* Read More Gaussian Process Models for Causal Inference With Time-Series Cross-Sectional Data
Matching Estimation for Causal Effect on Compositional Outcomes Kenichi Ariga ... Read More Matching Estimation for Causal Effect on Compositional Outcomes
