Weighted Lindley frailty model: estimation and application to lung cancer data

Mota, Alex; Milani, Eder A.; Calsavara, Vinicius F.; Tomazella, Vera L. D.; Leao, Jeremias; Ramos, Pedro L.; Ferreira, Paulo H.; Louzada, Francisco

Abstract

In this paper, we propose a novel frailty model for modeling unobserved heterogeneity present in survival data. Our model is derived by using a weighted Lindley distribution as the frailty distribution. The respective frailty distribution has a simple Laplace transform function which is useful to obtain marginal survival and hazard functions. We assume hazard functions of the Weibull and Gompertz distributions as the baseline hazard functions. A classical inference procedure based on the maximum likelihood method is presented. Extensive simulation studies are further performed to verify the behavior of maximum likelihood estimators under different proportions of right-censoring and to assess the performance of the likelihood ratio test to detect unobserved heterogeneity in different sample sizes. Finally, to demonstrate the applicability of the proposed model, we use it to analyze a medical dataset from a population-based study of incident cases of lung cancer diagnosed in the state of Sao Paulo, Brazil.

Más información

Título según WOS: Weighted Lindley frailty model: estimation and application to lung cancer data
Título de la Revista: LIFETIME DATA ANALYSIS
Volumen: 27
Número: 4
Editorial: Springer
Fecha de publicación: 2021
Página de inicio: 561
Página final: 587
DOI:

10.1007/S10985-021-09529-1

Notas: ISI