Testing Goodness-of-Fit of Parametric Survival Models for Right Censored Data

The main goal of this work it is to present a review of the existing methods to deal with the goodness-of-fit for right-censored data. Goodness-of-fit tests are developed to assess whether a given distribution is suited to a data set. Literature on goodness-of-fit tests for right-censored data is sc...

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Detalles Bibliográficos
Autor: Besalú Mayol, Mireia|||0000-0003-0473-2404
Tipo de recurso: tesis de maestría
Fecha de publicación:2016
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:2117/88820
Acceso en línea:https://hdl.handle.net/2117/88820
Access Level:acceso abierto
Palabra clave:Survival analysis (Biometry)
Goodness-of-fit
Right-censored
Chi-squared
Implementation
Anàlisi de supervivència (Biometria)
Classificació AMS::62 Statistics::62N Survival analysis and censored data
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
Descripción
Sumario:The main goal of this work it is to present a review of the existing methods to deal with the goodness-of-fit for right-censored data. Goodness-of-fit tests are developed to assess whether a given distribution is suited to a data set. Literature on goodness-of-fit tests for right-censored data is scarce and scattered. This master s degree thesis is divided into three different parts. The first part is devoted to review the bibliography of goodness-of-fit test for parametric models with right-censored data. We classify them according to the type of censoring and the methodology used, and we also propose a unified notation. The second part it focuses on the theoretic explanation of the Generalized Chi Squared test. Finally, the last part of the work presents an implementation in R of the Generalized Chi-Squared test for complete and right-censored data. We also have applied the above methods to some data sets and we have analyzed the results.