TY - JOUR
TI - Two-part quantile regression analysis with variable selection for complex data and its application
AU - Chen Ting
AU - Xiao Min
JN - Thermal Science
PY - 2025
VL - 29
IS - 3
SP - 2023
EP - 2030
PT - Article
AB - Semi-continuous data, also known as zero-inflated non-negative continuous  data, are commonly observed in various fields such as biomedicine,  environmental science, and ecology. Such data exhibit a combination of zero  values and positive continuous values that are right-skewed and  heteroscedastic. In this study, we present a novel approach for analyzing  complex semi-continuous data using a two-part quantile regression method. In  addition, we investigate variable selection techniques using least absolute  shrinkage and selection operator, smoothly clipped absolute deviation, and  minimax concave penalty methods within the framework of two-part quantile  regression. Simulation studies are then conducted to evaluate the  effectiveness of the proposed methods. Finally, we apply these methods to  examine the determinants of health care spending decisions in American  households.