Collaborative Research: Distributional Balancing Methods for Advancing Causal Inference in — NSF Award to University of Wisconsin-
Recent advances in data science and statistics have revolutionized how researchers uncover cause-and-effect relationships from complex, real-world data. Many pressing questions—such as whether flu vaccination reduces infection rates, whether sanitation programs improve children’s health, or whether educational policies
| Award title | Collaborative Research: Distributional Balancing Methods for Advancing Causal Inference in |
|---|---|
| Award ID | 2515263 |
| Awardee | University of Wisconsin-Madison |
| City | MADISON |
| State | WI |
| Amount obligated | $68,000 |
| Principal investigator | Guanhua Chen |
| Program | STATISTICS |
| Start date | 09/01/2025 |
| Abstract | Recent advances in data science and statistics have revolutionized how researchers uncover cause-and-effect relationships from complex, real-world data. Many pressing questions—such as whether flu vaccination reduces infection rates, whether sanitation programs improve children’s health, or whether educational policies enhance student outcomes—cannot be answered through randomized experiments alone. Observational data, while abundant, often pose serious challenges due to hidden biases, unmeasure |
| Source | NSF Awards |
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