Inference Based on Empirical Likelihood for Varying Coefficient Model with Random Effect

In this article, we develop a statistical inference technique for the unknown coefficient functions in the varying coefficient model with random effect. A residual-adjusted block empirical likelihood (RABEL) method is suggested to investigate the model by taking the within-subject correlation into account. Due to the residual adjustment, the proposed RABEL is asymptotically chi-squared distribution. We illustrate the large sample performance of the proposed method via Monte Carlo simulations and a real data application.