Colloquium - Fan Li
Institution: Duke University
Title: Balancing Covariates via Propensity Score Weighting in Causal Inference
Date: November 1, 2022
Location: Zoom (Click here for meeting details)
Time: 10:20 AM - 11:10 AM Eastern Time
Covariate balance is crucial for causal inference. However, lack of balance is common in observational studies. In this talk, we overview a general class of weighting strategies for balancing covariates: the balancing weights. These weights incorporate the propensity score to weight each group to an analyst-selected target population. This class unifies existing weighting methods, including inverse-probability weights as special cases. We introduce the overlap weighting (OW) scheme, in which each unit's weight is proportional to the probability of that unit being assigned to the opposite group. The overlap weights are bounded, minimize the asymptotic variance of the weighted average treatment effect among the class of balancing weights, and also possess a desirable small-sample exact balance property. The overlap weights target at the population in clinical equipoise, or more broadly, the population with substantial overlap in baseline characteristics between two groups. We illustrate the method by several real-world health studies.
Fan Li is a professor in the Departments of Statistical Science, and Biostatistics and Bioinformatics at Duke University. Her primary research interest is statistical methods for causal inference, with applications to health and social sciences. She also works on Bayesian analysis and missing data. She is an associate editor of Journal of the American Statistical Association, Bayesian Analysis, and Observational Studies.
Arkaprabha Ganguli, STT PhD candidate, received a 2022 IMS International Conference on Statistics and Data Science student travel award to present his work “Feature selection integrated deep learning for ultrahigh dimensional and highly correlated feature space.” In recognition of this award, his name appeared in the first page of the 2022 October/November issue of the IMS Bulletin https://imstat.org/wp-content/uploads/2022/07/Bulletin51_7.pdf .
Congratulations to PhD candidate Sarah Manski for winning first place for her oral presentation at the 2022 Conference on Applied Statistics in Agriculture and Natural Resources in May at Utah State University in Logan, Utah.
Abhijnan Chattopadhyay graduated from MSU with a Ph.D. in statistics this summer under the co-mentorship of Tapabrata Maiti and David Kramer. As a statistician, Abhijnan had the flexibility and skillset to work in several disciplines, which is how he found himself at the MSU-DOE Plant Research Laboratory (PRL).
PhD candidate Andriana Manousidaki was recently presented with the 2021-2022 William L. Harkness Award for outstanding teaching by a graduate student. The award is made possible by a generous gift from William Harkness, a doctoral alumnus from the Department of Statistics and Probability. Recipients are chosen for their remarkable teaching based on student evaluations and faculty observations of teaching.