معرفی
Nicole Pashley is an Assistant Professor in the Department of Statistics at Rutgers University, part of the School of Arts and Sciences. Her research focuses on causal inference, experimental design, and analysis using randomization-based frameworks. She holds a PhD from Harvard University's Department of Statistics (2020). Currently, she serves as Secretary/Treasurer for the ASA Section on Statistics in Epidemiology. Her work is supported by two NSF grants: SES 2217522 on 'Unpacking Compound Treatments in Email Audit Experiments' (with Tirthankar Dasgupta and Brian Libgober) and SES 2316908 on 'Causal Inference for Incomplete and Heterogeneous Multisite and Blocked Experiments.' Her research emphasizes design-based causal inference, experimental efficiency, and noncompliance analysis in factorial experiments. She is also involved in applied projects, such as pest control efficacy studies. Her office is located at Hill Center 477, Rutgers University, Piscataway, NJ.
Education: PhD in Statistics, Harvard University, 2020.
Research Interests: Nicole specializes in causal mechanisms and experimental design, particularly in complex treatment structures and audit experiments. Key areas include high-dimensional treatments, factorial experiments with noncompliance, and optimal sample allocation. She develops methodologies to improve causal effect estimation in heterogeneous populations and incomplete/multisite studies. Her work bridges theoretical statistics with practical applications in social and health sciences.
Grants: Her NSF-funded projects address email audit experiments and causal inference challenges in blocked/multisite studies. These grants support methodological advancements for analyzing compound treatments and heterogeneous effects.
Labs/Teams: As part of the Department of Statistics at Rutgers and her ASA leadership role, she collaborates with interdisciplinary teams to advance statistical methodologies in epidemiology and experimental design.
