title: Nonparametric and semiparametric regression estimation for length-biased survival data.
abstract: For the past several decades, nonparametric and semiparametric modeling for conventional right-censored survival data has been investigated intensively under a noninformative censoring mechanism. However, these methods may not be applicable for analyzing right-censored survival data that arise from prevalent cohorts when the failure times are subject to length-biased sampling. This review article is intended to provide a summary of some newly developed methods as well as established methods for analyzing length-biased data.
authors.affiliation: Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. yshen@mdanderson.org.
authors.forename: Yu
authors.initials: Y
authors.lastname: Shen
authors.affiliation: Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
authors.forename: Jing
authors.initials: J
authors.lastname: Ning
authors.affiliation: Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institute of Health, Bethesda, MD, 20892, USA.
authors.forename: Jing
authors.initials: J
authors.lastname: Qin
mesh_terms: D003627:Data Interpretation, Statistical; D006801:Humans; D015233:Models, Statistical; D016019:Survival Analysis
keywords: Estimating equation; Left truncation; Length-biased sampling; Likelihood; Nonparametric estimator; Semiparametric models