The nonparametric location-scale mixture cure model

• Justin Chown ^[1] ; Cédric Heuchenne ^[2] ; Ingrid Van Keilegom ^[3]
  1. [1] Ruhr University Bochum

     Ruhr University Bochum

     Kreisfreie Stadt Bochum, Alemania

     
  2. [2] University of Liège

     University of Liège

     Arrondissement de Liège, Bélgica

     
  3. [3] KU Leuven

     KU Leuven

     Arrondissement Leuven, Bélgica

     

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• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 29, Nº. 4, 2020, págs. 1008-1028
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • We propose completely nonparametric methodology to investigate location-scale modeling of two-component mixture cure models that is similar in spirit to accelerated failure time models, where the responses of interest are only indirectly observable due to the presence of censoring and the presence of long-term survivors that are always censored. We use nonparametric estimators of the location-scale model components that depend on a bandwidth sequence to propose an estimator of the error distribution function that has not been considered before in the literature. When this bandwidth belongs to a certain range of undersmoothing bandwidths, the proposed estimator of the error distribution function is root-n consistent. A simulation study investigates the finite sample properties of our approach, and the methodology is illustrated using data obtained to study the behavior of distant metastasis in lymph-node-negative breast cancer patients.