Kosuke Imai's Research Programs

 

Computational Social Science: This research program develops new statistical and machine learning tools for analyzing a variety of large data sets and solving computational problems that arise in social science research.
Design and Analysis of Randomized Experiments and Program Evaluation: This research program develops statistical tools for efficiently designing and analyzing randomized experiments in political science and public policy.
Elicitation of Truthful Answers to Sensitive Survey Questions: This research program develops new statistical models to analyze survey experiments for eliciting truthful answers to sensitive questions such as racial prejudice and support for militant groups.
Identification of Causal Mechanisms via Causal Mediation Analysis: This research program develops statistical analysis and research design strategies for identifying causal mechanisms in addition to causal effects.
Matching Methods for Causal Inference in Experimental and Observational Studies: This research program develops various matching methods, which allow researchers to compare units that are similar to each other except for the key causal variables of interest.
Propensity Score Methods for Causal Inference in Experimental and Observational Studies: This research program generalizes and improves propensity score methods, which allow researchers to obtain reliable estimates of causal effects in a variety of settings.

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 Last modified: Sat May 6 13:03:21 EDT 2017