Polynomial regression and estimation function in the presence of multiplication measurement error, with application to nutrition

Stephen J. Iturria, Raymond J. Carroll and David Firth

No 1997,10, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

Abstract: In this paper we consider the polynomial regression model in the presence of multiplicative measurement error in the predictor. Consistent parameter estimates and their associated standard errors are derived. Two general methods are considered, with the methods differing in their assumptions about the distributions of the predictor and the measurement errors. Data from a nutrition study are analyzed using the methods. Finally, the results from a simulation study are presented and the performances of the methods compared.

Keywords: Bootstrap; Measurement Error; Errors-in-Variables; Asymptotic theory; Estimating Equations; Nonlinear Regression; Nutrition (search for similar items in EconPapers)
Date: 1997
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb373:199710

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