Comparison of Weighted Estimation Methods for the Varying Coefficient Quantile Regression Model in the Case of Longitudinal Data
DOI:
https://doi.org/10.62933/q04zh103Keywords:
Longitudinal data analysis, , Quantile regression,, Weighted local polynomial,, Weighted SplineAbstract
In this study, two weighted methods are proposed for estimating the varying coefficient quantile regression model in the case of longitudinal data. The first method is the Weighted Spline Method, and the second is the Weighted Local Polynomial Method. Both methods account for within-subject correlations, which are addressed by incorporating weights derived from the empirical likelihood of each method. Five levels of quantiles were examined, and a simulation study was conducted to compare the two methods under different conditions. The methods were applied to the success rates data of the third intermediate grade in Al-Diwaniyah Governorate, assessing the impact of four explanatory variables on the success rates of 337 middle and secondary schools over five years. Results indicated that the efficiency of the methods varied across quantile levels: the Weighted Spline Method was more efficient at high and low quantile levels, whereas the Weighted Local Polynomial Method proved more efficient at intermediate levels.
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