Quadratic Inference Function Estimation in Partially Linear Measurement Error Models with Longitudinal Data

In this paper, we focus on the estimation for the marginal semiparametric partially linear models with longitudinal data when some covariates are measured with additive errors. We first approximate the nonparametric part of the model based on the B-splines and a new bias-corrected estimation procedure is proposed based on the quadratic inference functions (QIF). Under some regularity conditions, we show that the QIF estimator is consistent and asymptotically normal. Extensive simulation studies and an application are conducted to examine the finite sample performance of the proposed estimation procedure.