The article introduces a new evaluation model called a second order model with composite quantile regression. This model combines different statistical techniques to provide a complete assessment of relationships between variables at various levels. The researchers developed a modified estimation algorithm that can estimate these relationships accurately. The key finding is that this new model can give a comprehensive evaluation result based on all quantile levels, making it easier to understand complex data patterns.