Smooth-Threshold GEE Variable Selection Based on Quadratic Inference Functions with Longitudinal Data

A variable selection procedure is proposed using smooth-threshold generalized estimating equations based on quadratic inference functions (SGEE-QIF). The proposed procedure automatically eliminates inactive predictors by setting the corresponding parameters to be zero, and simultaneously estimates the nonzero regression coefficients by solving the SGEE-QIF. The proposed procedure avoids the convex optimization problem and is flexible and easy to implement. We establish the consistency and asymptotic normality of the resulting estimators. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed variable selection procedure.