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On estimation and diagnostics analysis in log-generalized gamma regression model for interval-censored data
Authors:Elizabeth M. Hashimoto  Vicente G. Cancho  Gauss M. Cordeiro
Affiliation:1. Departmento de Ciências Exatas , Universidade de S?o Paulo , Avenue Pádua Dias 11, Caixa Postal 9, 13418-900 , Piracicaba , S?o Paulo , Brazil;2. Departamento de Matemática Aplicada e Estatística , Universidade de S?o Paulo , Brazil;3. Departamento de Estatística , Universidade Federal de Pernambuco , Brazil
Abstract:
The interval-censored survival data appear very frequently, where the event of interest is not observed exactly but it is only known to occur within some time interval. In this paper, we propose a location-scale regression model based on the log-generalized gamma distribution for modelling interval-censored data. We shall be concerned only with parametric forms. The proposed model for interval-censored data represents a parametric family of models that has, as special submodels, other regression models which are broadly used in lifetime data analysis. Assuming interval-censored data, we consider a frequentist analysis, a Jackknife estimator and a non-parametric bootstrap for the model parameters. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and present some techniques to perform global influence.
Keywords:log-generalized gamma regression  generalized gamma distribution  interval-censored data  maximum likelihood  regression model  sensitivity analysis
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