What is it about?

Building on the recent statistical literature on randomized experiments, we offer general recommendations for designing and analyzing randomized experiments to improve validity and efficiency of inferring causality. We also develop a new statistical methodology that is then applied to a survey experiment conducted during Japan's 2004 Upper House election.

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Why is it important?

By developing a new statistical methodology, the validity and efficiency of causal inference are improved in randomized experiments, as well as the potential to explore causal heterogeneity. Included in the study is also an R package publicly available for implementing various methods useful for designing and analyzing randomized experiments.

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This page is a summary of: Designing and Analyzing Randomized Experiments: Application to a Japanese Election Survey Experiment, American Journal of Political Science, July 2007, Wiley, DOI: 10.1111/j.1540-5907.2007.00274.x.
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