Regression on Quantile Residual Life
Article first published online: 7 MAY 2009
© 2009, The International Biometric Society
Volume 65, Issue 4, pages 1203–1212, December 2009
How to Cite
Jung, S.-H., Jeong, J.-H. and Bandos, H. (2009), Regression on Quantile Residual Life. Biometrics, 65: 1203–1212. doi: 10.1111/j.1541-0420.2009.01196.x
- Issue published online: 23 NOV 2009
- Article first published online: 7 MAY 2009
- Received November 2007. Revised October 2008. Accepted October 2008.
- Breast cancer;
- Minimum dispersion statistic
Summary A time-specific log-linear regression method on quantile residual lifetime is proposed. Under the proposed regression model, any quantile of a time-to-event distribution among survivors beyond a certain time point is associated with selected covariates under right censoring. Consistency and asymptotic normality of the regression estimator are established. An asymptotic test statistic is proposed to evaluate the covariate effects on the quantile residual lifetimes at a specific time point. Evaluation of the test statistic does not require estimation of the variance–covariance matrix of the regression estimators, which involves the probability density function of the survival distribution with censoring. Simulation studies are performed to assess finite sample properties of the regression parameter estimator and test statistic. The new regression method is applied to a breast cancer data set with long-term follow-up to estimate the patients' median residual lifetimes, adjusting for important prognostic factors.