Biostatistics Student Seminar: David Whitney

Presentation: Evaluating Estimators when Modelling Assumptions Fail

Speaker: David Whitney, Graduate Student, UW Biostatistics

Abstract: In public health and other research areas, the difference in means, relative risk, odds ratio, hazard ratio, and other summary measures are frequently reported to describe the association between an outcome and exposure. Estimation of these measures of association often follows by assuming the data is generated from a simple parametric or semiparametric regression model, appealing to the idea that “all models are wrong, but some are useful.” We propose the use of techniques from the study of regular asymptotically linear estimators to derive the large-sample interpretation and behavior of an estimator in a general nonparametric model. This framework is illustrated through case studies of commonly used regression models, including linear regression, partial linear regression, and proportional hazards regression.

Wed, Jan 10, 2018, 3:30pm to 5:00pm
Room F-643 (HSF)

Student Coordinators: Phuong Vu, Arjun Sondhi, and Tyler Bonnett