… Tests used for checking convergence of a Bayesian … Gelman-Rubin Statistic, Bayesian
Gelman - Rubin diagnostic … to be significant factor which influence the survival of diabetic …

… how we conducted diagnostic checks for the simulated data in Section 3.2, we can also look
at a plot of the lag-1 autocorrelations for each of the Y s. A further diagnostic check is given …

… case-deletion influence diagnostics for survival models … Bayesian inference for the models;
In this section, some measures of model selection and Bayesian case influence diagnostics …

… In this paper, we propose a new bivariate cure rate survival model. Our approach enables …
are influential for the analysis, we considered a Bayesian case influence diagnostic procedure …

… The survival model incorporates a cure rate fraction and … , grade, marital status and age at
diagnosis being linked to its scale … about the covariates that may influence censoring, we used …

… For model comparison some Bayesian criteria were used. An influence diagnostic analysis
… with cure fraction, also known as long-term survival models or cure rate models, have been …

… of survival analysis, the failure rate function may frequently present a unimodal shape. In such
cases, … regression model based on the odd log-logistic Weibull distribution is proposed for …

… method and Bayesian approaches to identify risk factors that are assumed to influence the
survival of corona virus (covid-19) patients. … 2 we use tests like the parial likelihood ratio test. …

… assessed using standard diagnostic tools for survival models. The diagnostic tools can be
… assessment but in this paper we only focus on influence diagnostics, which was the main …

… An application to survival analysis shows that the GOLLEx distribution provides much …
influential observation(s) for the analysis we use the Bayesian case-deletion influence diagnostic …