Eric Tchetgen Tchetgen

Eric Tchetgen Tchetgen is a Professor of Biostatistics and Epidemiologic Methods with joint appointment in the departments of Biostatistics and Epidemiology at the Harvard T.H. Chan School of Public Health. His primary area of interest is in semi-parametric efficiency theory with application to causal inference, missing data problems, statistical genetics and mixed model theory. In general, he works on the development of statistical and epidemiologic methods that make efficient use of the information in data collected by scientific investigators, while avoiding unnecessary assumptions about the underlying data generating mechanism.

Title: "Minimax estimation of a nonlinear functional on a high-dimensional model"

Abstract: We introduce a new method of estimation of parameters in semi-parametric and nonparametric models. The method is based on U-statistics that are based on higher order influence functions that extend ordinary linear influence functions of the parameter of interest, and represent higher derivatives of this parameter. For parameters for which the representation cannot be perfect the method often leads to a bias-variance trade-off, and results in estimators that converge at a slower than root-n-rate. In a number of examples the resulting rate can be shown to be optimal. We are particularly interested in estimating parameters in models with a nuisance parameter of high dimension or low regularity, where the parameter of interest cannot be estimated at root-n-rate, but we also consider efficient root-n-estimation using novel nonlinear estimators. The general approach is applied in detail to several example inclduding estimation of a mean response when the response is not always observed and estimation of a treatment effect conditional on confounders under a semilinear model. This is joint work with James Robins, Aad van der Vaart, Lingling Li and Rajarshi Mukherjee.