Regression on quantile residual life.
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.
Jung
Sin-Ho
SH
Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina 27710, USA.
Jeong
Jong-Hyeon
JH
Bandos
Hanna
H
D001699:Biometry / Q000379:methods*; D001943:Breast Neoplasms / Q000401:mortality / Q000601:surgery; D016208:Databases, Factual; D005260:Female; D006801:Humans; D008017:Life Expectancy; D016014:Linear Models; D008207:Lymphatic Metastasis