Designing and analyzing randomized experiments: Application to a Japanese election survey experiment

Yusaku Horiuchi, Kosuke Imai, Naoko Taniguchi

研究成果: Article査読

55 被引用数 (Scopus)

抄録

Randomized experiments are becoming increasingly common in political science. 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. The proposed methods are applied to a survey experiment conducted during Japan's 2004 Upper House election, where randomly selected voters were encouraged to obtain policy information from political parties' websites. An R package is publicly available for implementing various methods useful for designing and analyzing randomized experiments.

本文言語English
ページ(範囲)669-687
ページ数19
ジャーナルAmerican Journal of Political Science
51
3
DOI
出版ステータスPublished - 2007 7
外部発表はい

ASJC Scopus subject areas

  • 社会学および政治科学
  • 政治学と国際関係論

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