Replication data for: Designing and Analyzing Randomized Experiments: Application to a Japanese Election Survey Experiment

Despite their well-known advantages over observational studies, randomized experiments are not free from complications. In particular, researchers often cannot force subjects to comply with treatment assignment and to provide the requested information.

Furthermore, simple randomization of treatments remains the most commonly used method in the discipline even though more efficient procedures are available. Building on the recent statistical literature, we address these methodological issues by offering general recommendations for designing and analyzing randomized experiments to improve the validity and efficiency of causal inference. We also develop a new statistical methodology to explore causal heterogeneity.