SAS/STAT Software


The QUANTLIFE procedure performs quantile regression analysis for survival data with censored data by using methods that are based on generalizations of the Kaplan-Meier and the Nelson-Aalen estimators. The following are highlights of the QUANTLIFE procedure's features:

  • supports hypothesis tests for the regression parameter
  • supports semiparametric quantile regression that uses spline effects
  • automatically creates survival plots, conditional quantile plots, and quantile process plots
  • supports classification variables
  • creates an output data set that contains predicted values and residuals
  • creates an output data set that contains survival function estimates or the conditional quantile function estimates for every set of covariates
  • supports an EFFECT statement that enables you to construct special collections of columns for design matrices
  • supports weighted quantile regression
  • computes confidence intervals for the quantile regression parameters by using resampling methods
  • uses an interior point algorithm for parameter estimation, which uses parallel computing when multiple processors are available
  • performs BY group processing, which enables you to obtain separate analyses of grouped observations

For further details see the QUANTLIFE Procedure