Identification and Estimation of Nonlinear Models Using Two Samples with Nonclassical Measurement Errors.

ABSTRACT: This paper considers identification and estimation of a general nonlinear Errors-in-Variables (EIV) model using two samples. Both samples consist of a dependent variable, some error-free covariates, and an error-prone covariate, for which the measurement error has unknown distribution and could be arbitrarily correlated with the latent true values; and neither sample contains an accurate measurement of the corresponding true variable. We assume that the regression model of interest - the conditional distribution of the dependent variable given the latent true covariate and the error-free covariates - is the same in both samples, but the distributions of the latent true covariates vary with observed error-free discrete covariates. We first show that the general latent nonlinear model is non

SUBMITTER: Carroll RJ 

PROVIDER: S-EPMC2873792 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature