Influence diagnostics for polyhazard models in the presence of covariates

Abstract

Polyhazard model, Poly-Weibull distribution, Poly-log-logistic distribution, Influence diagnostics, Residual analysis,

The Poisson-exponential regression model under different latent activation schemes

“…Diagnostic methods have been an important tool in survival regression analysis. Influential diagnostics should be investigated further in the context of the proposed Poisson-exponential regression model (Fachini et al, 2008).…”

A bivariate regression model with cure fraction

“…Also, some authors have investigated the assessment of local influence in survival analysis models. For instance, Pettitt and Bin Daud [32] investigated local influence in proportional hazard regression models, Escobar and Meeker [33] adapted local influence methods to regression analysis under censoring, Ortega et al [34] considered the problem of assessing local influence in generalized log-gamma regression models with censored observations, Fachini et al [35] proposed local influence methods to polyhazard models under the presence of explanatory variables, Silva et al [36] investigated global and local influences in log-Burr XII regression models with censored data and Carrasco et al [37] derived the appropriate matrices for assessing local influence in log-modified Weibull regression models with censored data. Furthermore, Ortega et al [25] adapted local influence methods to generalized log-gamma regression models with cure fraction and Hashimoto et al [38] investigated local influence in a log-exponentiated Weibull regression model for interval-censored data.…”

A bivariate regression model for matched paired survival data: local influence and residual analysis

“…Also, some authors have investigated the assessment of local influence in survival analysis models. For instance, Pettitt and Bin Daud (1989) investigated local influence in proportional hazard regression models, Escobar and Meeker (1992) adapted local influence methods to regression analysis with censoring, Ortega et al (2003) considered the problem of assessing local influence in generalized log-gamma regression models with censored observations, Ortega et al (2006) derived curvature calculations under various perturbation schemes in log-exponentiated Weibull regression models with censored data, Ortega et al (2008a) investigated local influence in the generalized log-gamma mixture model with covariates, Fachini et al (2008) adapted local influence methods to polyhazard models under the presence of explanatory variables, Silva et al (2008) investigate global and local influence in log-Burr XII regression models with censored data, Carrasco et al (2008) derived the appropriate matrices for assessing local influence in log-modified Weibull regression models with censored data and Ortega et al (2009) adapted local influence methods to generalized log-gamma regression models with a cure fraction. We propose a similar methodology to detect influential subjects; however, in bivariate regression models with censored data, based of the FGM copula.…”