Estimation in a semiparametric partially linear errors-in-variables model Academic Article

abstract

• We consider the partially linear model relating a response Y to predictors (X,T) with mean function XT + g(T) when the X's are measured with additive error. The semiparametric likelihood estimate of Severini and Staniswalis leads to biased estimates of both the parameter and the function g() when measurement error is ignored. We derive a simple modification of their estimator which is a semiparametric version of the usual parametric correction for attenuation. The resulting estimator of is shown to be consistent and its asymptotic distribution theory is derived. Consistent standard error estimates using sandwich-type ideas are also developed.

authors

• Carroll, Raymond

published proceedings

• ANNALS OF STATISTICS

author list (cited authors)

• Liang, H., Hardle, W., & Carroll, R. J.

citation count

• 254

complete list of authors

• Liang, Hua||Härdle, Wolfgang||Carroll, Raymond J

publication date

• October 1999

publisher

• Institute of Mathematical Statistics  Publisher

published in

• ANNALS OF STATISTICS  Journal

keywords

• Errors-in-variables
• Measurement Error
• Nonparametric Likelihood
• Orthogonal Regression
• Partially Linear Model
• Semiparametric Models
• Structural Relations

Digital Object Identifier (DOI)

• 10.1214/aos/1017939140

start page

• 1519

end page

• 1535

volume

• 27

issue

• 5

URL

• http%3A%2F%2Fdx.doi.org%2F10.1214%2Faos%2F1017939140