Analysis of longitudinal data using varying-coefficient model

In this study' a model selection procedure for varying-coefficient model based on longitudinal data is proposed to distinguish three types of variables: variables not in the model' variables in the model with time-independent coefficients and variables in the model with time-varying coefficients. To identify these three kinds of variables simultaneously' we extend the present variable selection method from cross-sectional data to longitudinal data. This method combines the B-spline function approximation and Adaptive-Lasso penalty to perform variable selection and do nonparametric estimation simultaneously. Validity is illustrated with a set of simulation experiments' and results indicate the proposed variable selection procedure performs well in distinguishing the real type of independent variables.