Competing risks methods
Competing risks data usually arises in studies in which the failure of an individual may be classified into one of k (k > 1) mutually exclusive causes of failure. When competing risks are present, classical survival analysis techniques may not be appropriate to use. The main goal of this paper is...
| Autores: | , , , |
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| Tipo de recurso: | informe técnico |
| Fecha de publicación: | 2007 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/2201 |
| Acceso en línea: | https://hdl.handle.net/2117/2201 |
| Access Level: | acceso abierto |
| Palabra clave: | Survival analysis (Biometry) Competing risks Cause-specific hazards Cumulative incidence functions Regression modelling Anàlisi de supervivència (Estadística) Classificació AMS::62 Statistics::62N Survival analysis and censored data Àrees temàtiques de la UPC::Matemàtiques i estadística |
| Sumario: | Competing risks data usually arises in studies in which the failure of an individual may be classified into one of k (k > 1) mutually exclusive causes of failure. When competing risks are present, classical survival analysis techniques may not be appropriate to use. The main goal of this paper is to review the specific methods to deal with competing risks. To this aim, we first focus on how to specify a competing risks model, which is the structure of observed data in this framework, and how components of the model are estimated from a given random sample. In addition, we discuss how to correctly interpret probabilities in the presence of competing risks, and regression models are considered in detail. To conclude, we illustrate the problem with data from a bladder cancer study. |
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