… Bayesian diagnostics, our goal is to develop a more general framework of Bayesian influence
analysis … the data for large classes of statistical models with or without missing data. So far, …

… the immune fraction and the influence of covariates on the at-risk fraction’s hazard rate [19,22,23]. …
As with the democratic regime survival application, we employed two tests, join count …

… prostate cancer survival models. The preoperative data set includes data on tests that were
… and basic machine learning tool, the naive Bayes classifier, can stand beside a mature and …

… case deletion diagnostics have been proposed to detect influential observations in various
parametric models … developed a case deletion influence diagnostic for survival models via the …

… In this article we propose a new cure rate survival model. In … we develop diagnostic studies
to detect possible influential or … model along with the development of an adequate Bayesian …

… rate survival model is developed under a scenario of latent competing causes (or risks). Our
model is a multivariate extension of the univariate survival … of the tests via a simulation study. …

… Table 4 presents model diagnostics statistics for all the fitted models. It is clear from the …
A number of factors at both individual and community levels have been identified to influence …

… The model is conceived inside a scenario of latent competing causes with the presence
of a … a Bayesian analysis for the proposed model. Case deletion influence diagnostics are …

… contains chapters on Bayesian survival analysis and use of … models, model-checking
diagnostics for parametric models … Some of the many areas of application of survival analysis are …

… substantially influenced breast cancer treatment standards. We implement the proposed …
after stratification by estrogen receptor status and inclusion of age at diagnosis in the model, …