“…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.…”