Penalized spline smoothing using Kaplan-Meier weights in semiparametric censored regression models

In this article we consider an extension of the penalized splines approach in the context of censored semiparametric modelling using Kaplan-Meier weights to take into account the effect of censorship. We proposed an estimation method and develop statistical inferences in the model. Using various sim...

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Detalles Bibliográficos
Autores: Orbe, Jesus, Virto, Jorge
Tipo de recurso: artículo
Fecha de publicación:2022
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:2117/397830
Acceso en línea:https://hdl.handle.net/2117/397830
https://dx.doi.org/10.2436/20.8080.02.119
Access Level:acceso abierto
Palabra clave:Survival analysis (Biometry)
censored data
Kaplan-Meier weights
P-splines
semiparametric models
survival analysis
62N Estadística de l'enginyeria
Classificació AMS::62 Statistics::62N Survival analysis and censored data
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
Descripción
Sumario:In this article we consider an extension of the penalized splines approach in the context of censored semiparametric modelling using Kaplan-Meier weights to take into account the effect of censorship. We proposed an estimation method and develop statistical inferences in the model. Using various simulation studies we show that the performance of the method is quite satisfactory. A real data set is used to illustrate that the proposed method is comparable to parametric approaches when assuming a probability distribution of the response variable and/or the functional form. However, our proposal does not need these assumptions since it avoids model specification problems.