Journal of Biometrics & Biostatistics

Jiaqing Chen

Publications

• Review Article
  Quantile Regression Models and Their Applications: A Review
  Author(s): Qi Huang, Hanze Zhang, Jiaqing Chen and Mengying HeQi Huang, Hanze Zhang, Jiaqing Chen and Mengying He
  
  Quantile regression (QR) has received increasing attention in recent years and applied to wide areas such as investment, finance, economics, medicine and engineering. Compared with conventional mean regression, QR can characterize the entire conditional distribution of the outcome variable, may be more robust to outliers and misspecification of error distribution, and provides more comprehensive statistical modeling than traditional mean regression. QR models could not only be used to detect heterogeneous effects of covariates at different quantiles of the outcome, but also offer more robust and complete estimates compared to the mean regression, when the normality assumption violated or outliers and long tails exist. These advantages make QR attractive and are extended to apply for different types of data, including independent data, time-to-event data and longitudinal data. Conseque.. Read More»
  DOI: 10.4172/2155-6180.1000354

  Abstract PDF