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Imai K, King G, Nall C. 2009. The essential role of pair matching in cluster-randomized experiments, with application to the Mexican universal health insurance evaluation. Statistical Science. 24:29–53.
Imai K, Strauss A. 2011. Estimation of heterogeneous treatment effects from randomized experiments, with application to the optimal planning of the get-out-the-vote campaign. Political Analysis. 19:1–19.
Imai K. 2005. Do get-out-the-vote calls reduce turnout? The importance of statistical methods for field experiments American Political Science Review. 99:283–300.
Imai K, King G, Nall C. 2009. Rejoinder: Matched Pairs and the Future of Cluster-Randomized Experiments. Statistical Science. :65–72.
Imai K. 2008. Sharp bounds on the causal effects in randomized experiments with “truncation-by-death”. Statistics & probability letters. 78:144–149.
Imai K, Keele L, Tingley D, Yamamoto T. 2011. Unpacking the black box of causality: Learning about causal mechanisms from experimental and observational studies. American Political Science Review. 105:765–789.
Imai K. 2007. Identification analysis for randomized experiments with noncompliance and truncation by death.
Imai K, Yamamoto T. 2013. Identification and sensitivity analysis for multiple causal mechanisms: Revisiting evidence from framing experiments. Political Analysis. 21:141–171.
Imai K, King G, Stuart EA. 2008. Misunderstandings between experimentalists and observationalists about causal inference. Journal of the Royal Statistical Society: Series A (Statistics in Society). 171:481–502.
Imai K. 2008. Variance identification and efficiency analysis in randomized experiments under the matched-pair design. Statistics in medicine. 27:4857–4873.
Imai K, Tingley D, Yamamoto T. 2013. Experimental designs for identifying causal mechanisms. Journal of the Royal Statistical Society, Series A. 176:5–51.
Imai K, Keele L, Tingley D. 2010. A general approach to causal mediation analysis.. Psychological methods. 15:309.
Imai K. 2009. Statistical analysis of randomized experiments with non-ignorable missing binary outcomes: an application to a voting experiment. Journal of the Royal Statistical Society: Series C (Applied Statistics). 58:83–104.