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Author Leao, J.; Leiva, V.; Saulo, H.; Tomazella, V. pdf  doi
  Title Birnbaum-Saunders frailty regression models: Diagnostics and application to medical data Type
  Year 2017 Publication Biometrical Journal Abbreviated Journal Biom. J.  
  Volume 59 Issue 2 Pages 291-314  
  Keywords Birnbaum-Saunders distribution; Censored data; Global and local influence; Maximum-likelihood method; Residual analysis  
  Abstract In survival models, some covariates affecting the lifetime could not be observed or measured. These covariates may correspond to environmental or genetic factors and be considered as a random effect related to a frailty of the individuals explaining their survival times. We propose a methodology based on a Birnbaum-Saunders frailty regression model, which can be applied to censored or uncensored data. Maximum-likelihood methods are used to estimate the model parameters and to derive local influence techniques. Diagnostic tools are important in regression to detect anomalies, as departures from error assumptions and presence of outliers and influential cases. Normal curvatures for local influence under different perturbations are computed and two types of residuals are introduced. Two examples with uncensored and censored real-world data illustrate the proposed methodology. Comparison with classical frailty models is carried out in these examples, which shows the superiority of the proposed model.  
  Address [Leao, Jeremias] Univ Fed Amazonas, Dept Stat, Manaus, Amazonas, Brazil, Email:  
  Corporate Author Thesis  
  Publisher Wiley Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0323-3847 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000396452500006 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 707  
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