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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.
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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.
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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.
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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.
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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. |