Smooth-threshold GEE variable selection for varying coefficient partially linear models with longitudinal data

In this paper, we consider the problem of variable selection for varying coefficient partially linear models with longitudinal data. A new variable selection procedure is proposed based on smooth-threshold generalized estimating equation (SGEE). The proposed procedure simultaneously selects significant variables in the parametric components and the nonparametric components. The approach avoids the convex optimization problem and is flexible and easy to implement. The consistency and asymptotic normality of the resulting estimators are established. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed variable selection procedure. The proposed procedure is further illustrated by an application.