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

• Jesus Orbe ^[1] ; Jorge Virto ^[1]
  1. [1] Universidad del País Vasco/Euskal Herriko Unibertsitatea

     Universidad del País Vasco/Euskal Herriko Unibertsitatea

     Leioa, España

     
• Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 46, Nº. 1, 2022, págs. 95-114
• Idioma: inglés
• Enlaces
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• Resumen

  • 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

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