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Activity Number: 371
Type: Contributed
Date/Time: Tuesday, August 4, 2009 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #304367
Title: Estimation in Covariate-Adjusted Nonlinear Regression Models
Author(s): Esra Kurum*+ and Damla Senturk
Companies: Penn State University and Penn State University
Address: 316 Thomas Building, University Park, PA, 16802,
Keywords: Varying Coefficient Models ; Local Polynomial Regression ; Multiplicative effects ; Nonlinear Regression
Abstract:

We propose a new estimation procedure for covariate adjusted nonlinear regression models for situations where both the predictors and response in a nonlinear regression model are not directly observed, however distorted versions of the predictors and response are observed. The distorted versions are assumed to be contaminated with a multiplicative factor that is determined by the value of an unknown function of an observable covariate. We demonstrate how the regression coefficients can be estimated by establishing a connection to nonlinear varying coefficient models. Simulation studies are used to illustrate the efficacy of the proposed estimation algorithm.

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