On estimation and diagnostics analysis in log-generalized gamma regression model for interval-censored data

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

Acknowledgements

We would like to thank the reviewers for the constructive comments. This study was supported by FAPESP Grant 2010/04496-2 and CNPq, Brazil.