Presentation: Non-iterative Estimation Update for Semiparametric Models with Population-based Auxiliary Information
Speaker: Fei Gao, Ph.D., Senior Fellow, Department of Biostatistics, University of Washington
Abstract: With the advancement in disease registries and surveillance data, population-based information on disease incidence, survival probability or other important biological characteristics become increasingly available. Such information can be leveraged in studies that collect detailed measurements but with smaller sample sizes. In contrast to recent proposals that formulate the additional information as constraints in optimization problems, we develop a general framework to construct simple estimators that update the usual regression estimators with some functionals of data that incorporate the additional information. We consider general settings which include nuisance parameters in the auxiliary information and semiparametric models with innite dimensional parameters. Detailed examples of several important settings are provided.