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. |