Empirical likelihood and quantile regression in longitudinal data analysis
纵向数据分析中的经验似然与分位数回归
We propose a novel quantile regression approach for longitudinal data analysis which naturally incorporates auxiliary information from the conditional mean model to account for within-subject correlations. The efficiency gain is quantified theoretically and demonstrated empirically via simulation studies and the analysis of a real dataset.