title: An introduction to survival models: in honor of Ross Prentice.
abstract: I review some key ideas and models in survival analysis with emphasis on modeling the effects of covariates on survival times. I focus on the proportional hazards model of Cox (J R Stat Soc B 34:187-220, 1972), its extensions and alternatives, including the accelerated life model. I briefly describe some models for competing risks data, multiple and repeated event-time data and multivariate survival data.
authors.affiliation: Department of Biostatistics and Computational Biology, University of Rochester Medical Center, 601 Elmwood Avenue, Box 630, 14642 , Rochester, NY, USA, oakes@bst.rochester.edu.
authors.forename: David
authors.initials: D
authors.lastname: Oakes
mesh_terms: D056808:Biostatistics / Q000266:history; D049673:History, 20th Century; D049674:History, 21st Century; D006801:Humans; D015233:Models, Statistical; D015999:Multivariate Analysis; D016016:Proportional Hazards Models; D012306:Risk; D016019:Survival Analysis