title: Cause-specific quantile residual life regression.
abstract: We propose a cause-specific quantile residual life regression where the cause-specific quantile residual life, defined as the inverse of the cumulative incidence function of the residual life distribution of a specific type of events of interest conditional on a fixed time point, is log-linear in observable covariates. The proposed test statistic for the effects of prognostic factors does not involve estimation of the improper probability density function of the cause-specific residual life distribution under competing risks. The asymptotic distribution of the test statistic is derived. Simulation studies are performed to assess the finite sample properties of the proposed estimating equation and the test statistic. The proposed method is illustrated with a real dataset from a clinical trial on breast cancer.
authors.affiliation: 1 Department of Public Health and Preventive Medicine, Oregon Health & Science University, Portland, USA.
authors.forename: Jeong Youn
authors.initials: JY
authors.lastname: Lim
authors.affiliation: 2 Department of Biostatistics, University of Pittsburgh, Pittsburgh, USA.
authors.forename: Jong-Hyeon
authors.initials: JH
authors.lastname: Jeong
mesh_terms: D001943:Breast Neoplasms / Q000401:mortality*; D005260:Female; D006801:Humans; D015994:Incidence; D011336:Probability; D011379:Prognosis; D012044:Regression Analysis; D012306:Risk; D015996:Survival Rate
keywords: Censored survival data; cause specific; competing risks; median; quantile regression; residual life