Testing for decreasing heterogeneity in a new time-varying frailty model

• Marco Munda ^[1] ; Catherine Legrand ^[1] ; Luc Duchateau ^[2] ; Paul Janssen ^[3]
  1. [1] Université Catholique de Louvain

     Université Catholique de Louvain

     Arrondissement de Nivelles, Bélgica

     
  2. [2] Ghent University

     Ghent University

     Arrondissement Gent, Bélgica

     
  3. [3] University of Hasselt

     University of Hasselt

     Arrondissement Hasselt, 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. 25, Nº. 4, 2016, págs. 591-606
• Idioma: inglés
• DOI: 10.1007/s11749-015-0468-9
• Texto completo no disponible (Saber más ...)
• Resumen

  • Frailty models adjust for between-cluster variability in survival data by including a cluster-specific random factor, the frailty term, in the Cox model. The frailty term is assumed to be constant over time. This assumption is questionable in some particular settings, e.g., in cancer clinical trials on chronic myeloid leukaemia. We therefore relax the time-constant heterogeneity assumption and consider frailty models with a time-varying frailty term. Instead of working with hazard models, we rather model the log cumulative hazard function, making use of the mixed model framework, and introduce a time-varying random effect at that level. Simulations demonstrate that the proposed method has acceptable size and power to detect time-dependent clustering. The method is applied to data from a large-scale multicentre clinical trial in patients with chronic myeloid leukaemia.