Locally efficient semiparametric estimators for functional measurement error models
Source: Biometrika, Volume 91, Number 4, December 2004 , pp. 835-848(14)
Publisher: Oxford University Press
Abstract:A class of semiparametric estimators are proposed in the general setting of functional measurement error models. The estimators follow from estimating equations that are based on the semiparametric efficient score derived under a possibly incorrect distributional assumption for the unobserved ‘measured with error’ covariates. It is shown that such estimators are consistent and asymptotically normal even with misspecification and are efficient if computed under the truth. The methods are demonstrated with a simulation study of a quadratic logistic regression model with measurement error.
Document Type: Research Article
Affiliations: 1: Department of Statistics, North Carolina State University, Raleigh, North Carolina 27695, U.S.A. , Email: firstname.lastname@example.org 2: Centre for Research in Scientific Computation, North Carolina State University, Raleigh, North Carolina 27695, U.S.A., Email: email@example.com
Publication date: 2004-12-01